25 research outputs found

    Ezetimibe/simvastatin 10/20 mg versus simvastatin 40 mg in coronary heart disease patients

    Get PDF
    BACKGROUND: Reducing low-density lipoprotein cholesterol (LDL-C) is the primary goal of therapy in patients with hypercholesterolemia and coronary heart disease (CHD). METHODS: This double blind placebo-controlled study enrolled patients 18 to 75 years of age with primary hypercholesterolemia and establishedCHDwhowere taking a stable daily dose of simvastatin 20 mg. Patients were randomized to ezetimibe/simvastatin 10/20 mg (eze/simva; n 5 56) or simvastatin 40 mg (simva; n 5 56) for 6 weeks. Percent change from baseline in LDL-C, total cholesterol, high-density lipoprotein cholesterol (HDL-C), and triglycerides were assessed by use of the Student t test. The percent of patients achieving LDL-C less than 100 mg/dL (,2.6mmol/L) or less than 80 mg/dL (,2.0 mmol/L) was analyzed via logistic regression with terms for treatment, baseline LDL-C, age, and gender. RESULTS: Baseline characteristics were similar between groups. Treatment with eze/simva combination resulted in significantly greater reductions in LDL-C, total cholesterol, and triglycerides versus doubling the dose of simva to 40 mg (all P , .01). Significantly more patients achieved LDL-C less than 100 mg/dL (,2.6mmol/L) and less than 80 mg/dL (,2.0mmol/L) with ezetimibe/simvastatin versus doubling the dose of simva to 40 mg (73.2% vs 25.0%; P,.001) for simvastatin. Changes in HDL-C were similar between treatments. Both treatments were generally well tolerated. CONCLUSION: In high-risk CHD patients with hypercholesterolemia, treatment with eze/simva combination resulted in significantly greater reductions inLDL-C, total cholesterol and triglycerides, as well as greater achievement of recommended LDL-C targets, compared with doubling the simvastatin dose to 40 mg over the 6-week period

    Examination of SmTRPA sequence for residues identified as important for drug activity.

    Get PDF
    <p>Alignments were made with ClustalW2 (<a href="http://www.ebi.ac.uk/Tools/msa/clustalw2/" target="_blank">http://www.ebi.ac.uk/Tools/msa/clustalw2/</a>) and Swiss-Model (<a href="http://swissmodel.expasy.org/" target="_blank">http://swissmodel.expasy.org/</a>). Numbering is based on the SmTRPA amino acid sequence. SmTRPA residues that are conserved are marked with a check mark (✓) above and are in bold and shaded, and those that are not conserved are marked with an x. <b>A.</b> Cysteine residues identified in mouse (equivalent to SmTRPA 407, 414, 611) or human (611, 631, 654) as important for activity of AITC and other electrophilic compounds on TRPA1 are shown. A lysine residue (K694) appears to be critical in human TRPA1 as well, and is also shown in bold and shaded. <b>B.</b> Residues identified as important for activity of vanilloid compounds on TRPV1 are not well conserved in SmTRPA. Of 4 residues thought to be important for capsaicin and other vanilloid activity, only the methionine/leucine residue at SmTRPA residue L824 appears to be conserved.</p

    A classical ergodic property for IFS: A simple proof

    No full text
    Let fw i ; p i g be a contractive IFS with probabilities. We provide a simple proof that for almost every address sequence oe and for all x the limit limn 1=n P in f \Gamma w oe n ffi w oe n\Gamma1 ffi \Delta \Delta \Delta ffi w oe 1 (x) \Delta exists and is equal to R X f(z) d¯(z) where ¯ is the invariant measure of the IFS. This is the so called &quot;ergodic property&quot; for the IFS and was proved by Elton in [3]. However, the uniqueness of the invariant measure was not previously exploited. This provides considerable simplification to the proof. Let X be a compact metric space and fw i g L i=1 a collection of L contraction maps on X. Let fp i g be a collection of L probabilities (i.e. P i p i = 1). In [4] Hutchinson proves that there exists a unique measure ¯ invariant under the Markov operator M defined by M ()(B) = X i p i (w \Gamma1 i (B)) where is a probability measure on X and B is a Borel subset of X. In fact M n () ! ¯ for any probability measure since the w ..
    corecore