Interfering with the connection between the nucleus and the cytoskeleton affects nuclear rotation, mechanotransduction and myogenesis

Mechanical stress controls a broad range of cellular functions. The cytoskeleton is physically connected to the extracellular matrix via integrin receptors, and to the nuclear lamina by the LINC complex that spans both nuclear membranes. We asked here how disruption of this direct link from the cytoskeleton to nuclear chromatin affects mechanotransduction. Fibroblasts grown on flexible silicone membranes reacted to cyclic stretch by nuclear rotation. This rotation was abolished by inhibition of actomyosin contraction as well as by overexpression of dominant-negative versions of nesprin or sun proteins that form the LINC complex. In an in vitro model of muscle differentiation, cyclic strain inhibits differentiation and induces proliferation of C2C12 myoblasts. Interference with the LINC complex in these cells abrogated their stretch-induced proliferation, while stretch increased p38 MAPK and NFkappaB phosphorylation and the transcript levels of myogenic transcription factors MyoD and myogenin. We found that the physical link from the cytoskeleton to the nuclear lamina is crucial for correct mechanotransduction, and that disruption of the LINC complex perturbs the mechanical control of cell differentiation.

Sample size estimation: an overview with applications to orthodontic clinical trial designs

Proper sample size estimation is an important part of clinical trial methodology and closely related to the precision and power of the trial's results. Trials with sufficient sample sizes are scientifically and ethically justified and more credible compared with trials with insufficient sizes. Planning clinical trials with inadequate sample sizes might be considered as a waste of time and resources, as well as unethical, since patients might be enrolled in a study in which the expected results will not be trusted and are unlikely to have an impact on clinical practice. Because of the low emphasis of sample size calculation in clinical trials in orthodontics, it is the objective of this article to introduce the orthodontic clinician to the importance and the general principles of sample size calculations for randomized controlled trials to serve as guidance for study designs and as a tool for quality assessment when reviewing published clinical trials in our specialty. Examples of calculations are shown for 2-arm parallel trials applicable to orthodontics. The working examples are analyzed, and the implications of design or inherent complexities in each category are discussed.

Comparison of variable-thread tapered implant designs to a standard tapered implant design after immediate loading. A 3-year multicentre randomised controlled trial

This randomised, controlled multicentre trial aimed at comparing two versions of a variable-thread dental implant design to a standard tapered dental implant design in cases of immediate functional loading for 36 months after loading.

Effective Length K-Factors For Flexural Buckling Strengths Of Web Members In Open Web Steel Joists

Open web steel joists are designed in the United States following the governing specification published by the Steel Joist Institute. For compression members in joists, this specification employs an effective length factor, or K-factor, in confirming their adequacy. In most cases, these K-factors have been conservatively assumed equal to 1.0 for compression web members, regardless of the fact that intuition and limited experimental work indicate that smaller values could be justified. Given that smaller K-factors could result in more economical designs without a loss in safety, the research presented in this thesis aims to suggest procedures for obtaining more rational values. Three different methods for computing in-plane and out-of-plane K-factors are investigated, including (1) a hand calculation method based on the use of alignment charts, (2) computational critical load (eigenvalue) analyses using uniformly distributed loads, and (3) computational analyses using a compressive strain approach. The latter method is novel and allows for computing the individual buckling load of a specific member within a system, such as a joist. Four different joist configurations are investigated, including an 18K3, 28K10, and two variations of a 32LH06. Based on these methods and the very limited number of joists studied, it appears promising that in-plane and out-of-plane K-factors of 0.75 and 0.85, respectively, could be used in computing the flexural buckling strength of web members in routine steel joist design. Recommendations for future work, which include systematically investigating a wider range of joist configurations and connection restraint, are provided.

Coffee inhibits the reactivation of glucocorticoids by 11beta-hydroxysteroid dehydrogenase type 1: a glucocorticoid connection in the anti-diabetic action of coffee?

Recent epidemiological studies demonstrated a beneficial effect of coffee consumption for the prevention of type 2 diabetes, however, the underlying mechanisms remained unknown. We demonstrate that coffee extract, corresponding to an Italian Espresso, inhibits recombinant and endogenous 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) activity. The inhibitory component is heat-stable with considerable polarity. Coffee extract blocked 11beta-HSD1-dependent cortisol formation, prevented the subsequent nuclear translocation of the glucocorticoid receptor and abolished glucocorticoid-induced expression of the key gluconeogenic enzyme phosphoenolpyruvate carboxykinase. We suggest that at least part of the anti-diabetic effects of coffee consumption is due to inhibition of 11beta-HSD1-dependent glucocorticoid reactivation.

THE ROLE OF AN EXPLICIT CAUSAL FRAMEWORK IN AFFECTED SIB PAIR DESIGNS WITH COVARIATES

The affected sib/relative pair (ASP/ARP) design is often used with covariates to find genes that can cause a disease in pathways other than through those covariates. However, such "covariates" can themselves have genetic determinants, and the validity of existing methods has so far only been argued under implicit assumptions. We propose an explicit causal formulation of the problem using potential outcomes and principal stratification. The general role of this formulation is to identify and separate the meaning of the different assumptions that can provide valid causal inference in linkage analysis. This separation helps to (a) develop better methods under explicit assumptions, and (b) show the different ways in which these assumptions can fail, which is necessary for developing further specific designs to test these assumptions and confirm or improve the inference. Using this formulation in the specific problem above, we show that, when the "covariate" (e.g., addiction to smoking) also has genetic determinants, then existing methods, including those previously thought as valid, can declare linkage between the disease and marker loci even when no such linkage exists. We also introduce design strategies to address the problem.

Designs in Partially Controlled Studies: Messages from a Review

The ability to evaluate effects of factors on outcomes is increasingly important for a class of studies that control some but not all of the factors. Although important advances have been made in methods of analysis for such partially controlled studies,work on designs for such studies has been relatively limited. To help understand why, we review main designs that have been used for such partially controlled studies. Based on the review, we give two complementary reasons that explain the limited work on such designs, and suggest a new direction in this area.