Judicial disagreement need not be political: dissent on the Estonian Supreme Court

I investigate the non-unanimous decisions of judges on the Estonian Supreme Court. I argue that since judges on the court enjoy high de jure independence, dissent frequently, and are integrated in the normal judicial hierarchy, the Estonian Supreme Court is a crucial case for the presumption that judicial disagreement reveals policy preferences. I analyse dissenting opinions using an ideal point response model. Examining the characteristics of cases which discriminated with respect to the recovered dimension, I show that this dimension cannot be interpreted as a meaningful policy dimension, but instead reflects disagreement about the proper scope of constitutional redress

Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy

Contains fulltext : 75361.pdf (publisher's version ) (Open Access)14 p

Mass spectrometry and multivariate analysis to classify cervical intraepithelial neoplasia from blood plasma: an untargeted lipidomic study

Cervical cancer is still an important issue of public health since it is the fourth most frequent type of cancer in women worldwide. Much effort has been dedicated to combating this cancer, in particular by the early detection of cervical pre-cancerous lesions. For this purpose, this paper reports the use of mass spectrometry coupled with multivariate analysis as an untargeted lipidomic approach to classifying 76 blood plasma samples into negative for intraepithelial lesion or malignancy (NILM, n = 42) and squamous intraepithelial lesion (SIL, n = 34). The crude lipid extract was directly analyzed with mass spectrometry for untargeted lipidomics, followed by multivariate analysis based on the principal component analysis (PCA) and genetic algorithm (GA) with support vector machines (SVM), linear (LDA) and quadratic (QDA) discriminant analysis. PCA-SVM models outperformed LDA and QDA results, achieving sensitivity and specificity values of 80.0% and 83.3%, respectively. Five types of lipids contributing to the distinction between NILM and SIL classes were identified, including prostaglandins, phospholipids, and sphingolipids for the former condition and Tetranor-PGFM and hydroperoxide lipid for the latter. These findings highlight the potentiality of using mass spectrometry associated with chemometrics to discriminate between healthy women and those suffering from cervical pre-cancerous lesions

Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening

Neuroendocrine–immune disequilibrium and endometriosis: an interdisciplinary approach

Endometriosis, a chronic disease characterized by endometrial tissue located outside the uterine cavity, affects one fourth of young women and is associated with chronic pelvic pain and infertility. However, an in-depth understanding of the pathophysiology and effective treatment strategies of endometriosis is still largely elusive. Inadequate immune and neuroendocrine responses are significantly involved in the pathophysiology of endometriosis, and key findings are summarized in the present review. We discuss here the role of different immune mechanisms particularly adhesion molecules, protein–glycan interactions, and pro-angiogenic mediators in the development and progression of the disease. Finally, we introduce the concept of endometrial dissemination as result of a neuroendocrine-immune disequilibrium in response to high levels of perceived stress caused by cardinal clinical symptoms of endometriosis

Efficacy and safety of oral semaglutide in patients with type 2 diabetes and moderate renal impairment (PIONEER 5): a placebo-controlled, randomised, phase 3a trial

Background: Oral semaglutide is the first oral glucagon-like peptide-1 (GLP-1) receptor agonist for glycaemic control in patients with type 2 diabetes. Type 2 diabetes is commonly associated with renal impairment, restricting treatment options. We aimed to investigate the efficacy and safety of oral semaglutide in patients with type 2 diabetes and moderate renal impairment. Methods: This randomised, double-blind, phase 3a trial was undertaken at 88 sites in eight countries. Patients aged 18 years and older, with type 2 diabetes, an estimated glomerular filtration rate of 30–59 mL/min per 1·73 m2, and who had been receiving a stable dose of metformin or sulfonylurea, or both, or basal insulin with or without metformin for the past 90 days were eligible. Participants were randomly assigned (1:1) by use of an interactive web-response system, with stratification by glucose-lowering medication and renal function, to receive oral semaglutide (dose escalated to 14 mg once daily) or matching placebo for 26 weeks, in addition to background medication. Participants and site staff were masked to assignment. Two efficacy-related estimands were defined: treatment policy (regardless of treatment discontinuation or rescue medication) and trial product (on treatment without rescue medication) in all participants randomly assigned. Endpoints were change from baseline to week 26 in HbA1c (primary endpoint) and bodyweight (confirmatory secondary endpoint), assessed in all participants with sufficient data. Safety was assessed in all participants who received at least one dose of study drug. This trial is registered on ClinicalTrials.gov, number NCT02827708, and the European Clinical Trials Registry, number EudraCT 2015-005326-19, and is now complete. Findings: Between Sept 20, 2016, and Sept 29, 2017, of 721 patients screened, 324 were eligible and randomly assigned to oral semaglutide (n=163) or placebo (n=161). Mean age at baseline was 70 years (SD 8), and 168 (52%) of participants were female. 133 (82%) participants in the oral semaglutide group and 141 (88%) in the placebo group completed 26 weeks on treatment. At 26 weeks, oral semaglutide was superior to placebo in decreasing HbA1c (estimated mean change of −1·0 percentage point (SE 0·1; −11 mmol/mol [SE 0·8]) vs −0·2 percentage points (SE 0·1; −2 mmol/mol [SE 0·8]); estimated treatment difference [ETD]: −0·8 percentage points, 95% CI −1·0 to −0·6;