Can dysglycemia in OGTT be predicted by baseline parameters in patients with PCOS?

BackgroundPolycystic ovary syndrome (PCOS) is considered a risk factor for the development of type 2 diabetes mellitus (T2DM). However, which is the most appropriate way to evaluate dysglycemia in women with PCOS and who are at increased risk are as yet unclear. Aim of the studyTo determine the prevalence of T2DM, impaired glucose tolerance (IGT), and impaired fasting glucose (IFG) in PCOS women and potential factors to identify those at risk. Subjects and methodsThe oral glucose tolerance test (OGTT), biochemical/hormonal profile, and ovarian ultrasound data from 1614 Caucasian women with PCOS and 362 controls were analyzed in this cross-sectional multicenter study. The data were categorized according to age and BMI. ResultsDysglycemia (T2DM, IGT, and IFG according to World Health Organization criteria) was more frequent in the PCOS group compared to controls: 2.2% vs 0.8%, P = 0.04; 9.5% vs 7.4%, P = 0.038; 14.2% vs 9.1%, P = 0.002, respectively. OGTT was essential for T2DM diagnosis, since in 88% of them basal glucose values were inconclusive for diagnosis. The presence of either T2DM or IFG was irrespective of age (P = 0.54) and BMI (P = 0.32), although the latter was associated with IGT (P = 0.021). There was no impact of age and BMI status on the prevalence of T2DM or IFG. Regression analysis revealed a role for age, BMI, fat deposition, androgens, and insulin resistance for dysglycemia. However, none of the factors prevailed as a useful marker employed in clinical practice. ConclusionsOne-third of our cohort of PCOS women with either T2DM or IGT displayed normal fasting glucose values but without confirming any specific predictor for dysglycemic condition. Hence, the evaluation of glycemic status using OGTT in all women with PCOS is strongly supported

BioMaPS: A Roadmap for Success

The manuscript outlines the impact that our National Science Foundation Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences program, BioMaPS, has had on the students and faculty at Murray State University. This interdisciplinary program teams mathematics and biology undergraduate students with mathematics and biology faculty and has produced research insights and curriculum developments at the intersection of these two disciplines. The goals, structure, achievements, and curriculum initiatives are described in relation to the effects they have had to enhance the study of biomathematics

Everolimus for patients with mantle cell lymphoma refractory to or intolerant of bortezomib: multicentre, single‐arm, phase 2 study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106815/1/bjh12780.pd

Connecting Biology and Mathematics: First Prepare the Teachers

Developing the connection between biology and mathematics is one of the most important ways to shift the paradigms of both established science disciplines. However, adding some mathematic content to biology or biology content to mathematics is not enough but must be accompanied by development of suitable pedagogical models. I propose a model of pedagogical mathematical biological content knowledge as a feasible starting point for connecting biology and mathematics in schools and universities. The process of connecting these disciplines should start as early as possible in the educational process, in order to produce prepared minds that will be able to combine both disciplines at graduate and postgraduate levels of study. Because teachers are a crucial factor in introducing innovations in education, the first step toward such a goal should be the education of prospective and practicing elementary and secondary school teachers

New 2,6,9-trisubstituted adenines as adenosine receptor antagonists: a preliminary SAR profile

A new series of 2,6,9-trisubstituted adenines (5–14) have been prepared and evaluated in radioligand binding studies for their affinity at the human A1, A2A and A3 adenosine receptors and in adenylyl cyclase experiments for their potency at the human A2B subtype. From this preliminary study the conclusion can be drawn that introduction of bulky chains at the N6 position of 9-propyladenine significantly increased binding affinity at the human A1 and A3 adenosine receptors, while the presence of a chlorine atom at the 2 position resulted in a not univocal effect, depending on the receptor subtype and/or on the substituent present in the N6 position. However, in all cases, the presence in the 2 position of a chlorine atom favoured the interaction with the A2A subtype. These results demonstrated that, although the synthesized compounds were found to be quite inactive at the human A2B subtype, adenine is a useful template for further development of simplified adenosine receptor antagonists with distinct receptor selectivity profiles

Modular Mass Spectrometric Tool for Analysis of Composition and Phosphorylation of Protein Complexes

The combination of high accuracy, sensitivity and speed of single and multiple-stage mass spectrometric analyses enables the collection of comprehensive sets of data containing detailed information about complex biological samples. To achieve these properties, we combined two high-performance matrix-assisted laser desorption ionization mass analyzers in one modular mass spectrometric tool, and applied this tool for dissecting the composition and post-translational modifications of protein complexes. As an example of this approach, we here present studies of the Saccharomyces cerevisiae anaphase-promoting complexes (APC) and elucidation of phosphorylation sites on its components. In general, the modular concept we describe could be useful for assembling mass spectrometers operating with both matrix-assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) ion sources into powerful mass spectrometric tools for the comprehensive analysis of complex biological samples

A simple algebraic cancer equation: calculating how cancers may arise with normal mutation rates

<p>Abstract</p> <p>Background</p> <p>The purpose of this article is to present a relatively easy to understand cancer model where transformation occurs when the first cell, among many at risk within a colon, accumulates a set of driver mutations. The analysis of this model yields a simple algebraic equation, which takes as inputs the number of stem cells, mutation and division rates, and the number of driver mutations, and makes predictions about cancer epidemiology.</p> <p>Methods</p> <p>The equation [<it>p </it>= 1 - (1 - (1 - (1 - <it>u</it>)^<it>d</it>)^<it>k</it>)^{<it>Nm </it>}] calculates the probability of cancer (<it>p</it>) and contains five parameters: the number of divisions (<it>d</it>), the number of stem cells (<it>N </it>× <it>m</it>), the number of critical rate-limiting pathway driver mutations (<it>k</it>), and the mutation rate (<it>u</it>). In this model progression to cancer "starts" at conception and mutations accumulate with cell division. Transformation occurs when a critical number of rate-limiting pathway mutations first accumulates within a single stem cell.</p> <p>Results</p> <p>When applied to several colorectal cancer data sets, parameter values consistent with crypt stem cell biology and normal mutation rates were able to match the increase in cancer with aging, and the mutation frequencies found in cancer genomes. The equation can help explain how cancer risks may vary with age, height, germline mutations, and aspirin use. APC mutations may shorten pathways to cancer by effectively increasing the numbers of stem cells at risk.</p> <p>Conclusions</p> <p>The equation illustrates that age-related increases in cancer frequencies may result from relatively normal division and mutation rates. Although this equation does not encompass all of the known complexity of cancer, it may be useful, especially in a teaching setting, to help illustrate relationships between small and large cancer features.</p

Singular vectors of orthogonally decomposable tensors

Orthogonal decomposition of tensors is a generalization of the singular value decomposition of matrices. In this paper, we study the spectral theory of orthogonally decomposable tensors. For such a tensor, we give a description of its singular vector tuples as a variety in a product of projective spaces

Duality of graphical models and tensor networks

In this article we show the duality between tensor networks and undirected graphical models with discrete variables. We study tensor networks on hypergraphs, which we call tensor hypernetworks. We show that the tensor hypernetwork on a hypergraph exactly corresponds to the graphical model given by the dual hypergraph. We translate various notions under duality. For example, marginalization in a graphical model is dual to contraction in the tensor network. Algorithms also translate under duality. We show that belief propagation corresponds to a known algorithm for tensor network contraction. This article is a reminder that the research areas of graphical models and tensor networks can benefit from interaction