Oxandrolone is an androgen and synthetic anabolic steroid (AAS) medication to help promote weight gain in various situations, to help offset protein catabolism caused by long-term corticosteroid therapy, to support recovery from severe burns, to treat bone pain associated with osteoporosis, to aid in the development of girls with Turner syndrome, and for other indications. It is taken by mouth. It was sold under the brand names Oxandrin and Anavar, among others.

Neurological diseases, particularly in the context of aging, have serious impacts on quality of life and can negatively affect bone health. The brain-bone ax...

Myocardial stents (both bare metal and drug-eluting varieties) are widely utilized to prevent restenosis following percutaneous transluminal coronary angioplasty (PTCA) and coronary intervention (PCI). Indeed, by 1999 myocardial stents were...

A future where we can control cars or smartphones solely with the power of thought is round the corner — but the price may be invasive surgery.

According to the pharmacist NO they don't, but I'm having more and more pain everyday since I started taking them again. Does anyone know if they are suppose to be safe or not? Thanks so much to anyone who can help on this one!!

There has been a great evolution in the development of coronary stents in order to avoid both restenosis and thrombosis. Improvements have led to improvements in the design and conformation

Background Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. Results With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. Conclusions pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

AbstractBACKGROUND. Estrogens regulate growth hormone (GH) secretion and modulate the tissue responsiveness to GH. After the menopause, and during ageing,

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Abstract. Summary: ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It features over