Whether to report diabetes as the underlying cause-of-death? a survey of internists of different sub-specialties

<p>Abstract</p> <p>Background</p> <p>Cause-specific mortality is a commonly used endpoint of clinical trials or prospective studies. However, it is sometimes difficult for physician to determine the underlying-cause-of-death (UCD), especially for diabetic patients coexisted with cardiovascular diseases (CVD). The aim of this survey was to examine whether internists with different specialties have different opinions on the reporting of diabetes as the UCD.</p> <p>Methods</p> <p>A total of 549 physicians completed the questionnaire in Taiwan, which comprised seven hypothetical case scenarios, each indicating a different level of contribution of diabetes in initiating the chain of events leading to death.</p> <p>Results</p> <p>As a whole, endocrinologists were more likely than cardiologists and nephrologists to report diabetes as the UCD. The differences were more prominent when the diabetic patient had a coexisting CVD. In scenario 3 (a diabetic patient with hypertension who died from acute myocardial infarction), the percentage was 56% in endocrinologists, which was significantly higher than in cardiologists (42%) and nephrologists (41%). In scenario 4 (a diabetic patient with hypertension who died from cerebrovascular infarction), the percentage was 45% in endocrinologists, and only 31% in cardiologists and 36% in nephrologists.</p> <p>Conclusions</p> <p>Internists of different sub-specialties do have different opinions on the reporting of diabetes as the UCD, especially when the diabetic patient has a coexisting CVD.</p

Heart rate variability and target organ damage in hypertensive patients

Background: We evaluated the association between linear standard Heart Rate Variability (HRV) measures and vascular, renal and cardiac target organ damage (TOD). Methods: A retrospective analysis was performed including 200 patients registered in the Regione Campania network (aged 62.4 ± 12, male 64%). HRV analysis was performed by 24-h holter ECG. Renal damage was assessed by estimated glomerular filtration rate (eGFR), vascular damage by carotid intima-media thickness (IMT), and cardiac damage by left ventricular mass index. Results: Significantly lower values of the ratio of low to high frequency power (LF/HF) were found in the patients with moderate or severe eGFR (p-value < 0.001). Similarly, depressed values of indexes of the overall autonomic modulation on heart were found in patients with plaque compared to those with a normal IMT (p-value <0.05). These associations remained significant after adjustment for other factors known to contribute to the development of target organ damage, such as age. Moreover, depressed LF/HF was found also in patients with left ventricular hypertrophy but this association was not significant after adjustment for other factors. Conclusions: Depressed HRV appeared to be associated with vascular and renal TOD, suggesting the involvement of autonomic imbalance in the TOD. However, as the mechanisms by which abnormal autonomic balance may lead to TOD, and, particularly, to renal organ damage are not clearly known, further prospective studies with longitudinal design are needed to determine the association between HRV and the development of TOD

Exposure to arsenic in drinking water is associated with increased prevalence of diabetes: a cross-sectional study in the Zimapán and Lagunera regions in Mexico

<p>Abstract</p> <p>Background</p> <p>Human exposures to inorganic arsenic (iAs) have been linked to an increased risk of diabetes mellitus. Recent laboratory studies showed that methylated trivalent metabolites of iAs may play key roles in the diabetogenic effects of iAs. Our study examined associations between chronic exposure to iAs in drinking water, metabolism of iAs, and prevalence of diabetes in arsenicosis-endemic areas of Mexico.</p> <p>Methods</p> <p>We used fasting blood glucose (FBG), fasting plasma insulin (FPI), oral glucose tolerance test (OGTT), glycated hemoglobin (HbA1c), and insulin resistance (HOMA-IR) to characterize diabetic individuals. Arsenic levels in drinking water and urine were determined to estimate exposure to iAs. Urinary concentrations of iAs and its trivalent and pentavalent methylated metabolites were measured to assess iAs metabolism. Associations between diabetes and iAs exposure or urinary metabolites of iAs were estimated by logistic regression with adjustment for age, sex, hypertension and obesity.</p> <p>Results</p> <p>The prevalence of diabetes was positively associated with iAs in drinking water (OR 1.13 per 10 ppb, p < 0.01) and with the concentration of dimethylarsinite (DMAs^III) in urine (OR 1.24 per inter-quartile range, p = 0.05). Notably, FPI and HOMA-IR were negatively associated with iAs exposure (β -2.08 and -1.64, respectively, p < 0.01), suggesting that the mechanisms of iAs-induced diabetes differ from those underlying type-2 diabetes, which is typically characterized by insulin resistance.</p> <p>Conclusions</p> <p>Our study confirms a previously reported, but frequently questioned, association between exposure to iAs and diabetes, and is the first to link the risk of diabetes to the production of one of the most toxic metabolites of iAs, DMAs^III.</p

Difference-based clustering of short time-course microarray data with replicates

<p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p

Interaction between Amyloid Beta Peptide and an Aggregation Blocker Peptide Mimicking Islet Amyloid Polypeptide

Assembly of amyloid-beta peptide (Aβ) into cytotoxic oligomeric and fibrillar aggregates is believed to be a major pathologic event in Alzheimer's disease (AD) and interfering with Aβ aggregation is an important strategy in the development of novel therapeutic approaches. Prior studies have shown that the double N-methylated analogue of islet amyloid polypeptide (IAPP) IAPP-GI, which is a conformationally constrained IAPP analogue mimicking a non-amyloidogenic IAPP conformation, is capable of blocking cytotoxic self-assembly of Aβ. Here we investigate the interaction of IAPP-GI with Aβ40 and Aβ42 using NMR spectroscopy. The most pronounced NMR chemical shift changes were observed for residues 13–20, while residues 7–9, 15–16 as well as the C-terminal half of Aβ - that is both regions of the Aβ sequence that are converted into β-strands in amyloid fibrils - were less accessible to solvent in the presence of IAPP-GI. At the same time, interaction of IAPP-GI with Aβ resulted in a concentration-dependent co-aggregation of Aβ and IAPP-GI that was enhanced for the more aggregation prone Aβ42 peptide. On the basis of the reduced toxicity of the Aβ peptide in the presence of IAPP-GI, our data are consistent with the suggestion that IAPP-GI redirects Aβ into nontoxic “off-pathway” aggregates

Properties of Graphene: A Theoretical Perspective

In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic

Caveolin-1 enhances resveratrol-mediated cytotoxicity and transport in a hepatocellular carcinoma model

<p>Abstract</p> <p>Background</p> <p>Resveratrol (RES), an estrogen analog, is considered as a potential cancer chemo-preventive agent. However, it remains unclear how RES is transported into cells. In this study, we observed that Caveolin-1(CAV1) expression can increase the cytotoxic and pro-apoptotic activity of RES in a dose- and time-dependent manner both <it>in vitro </it>and <it>in vivo </it>in a Hepatocellular Carcinoma animal model.</p> <p>Methods</p> <p>High performance liquid chromatography (HPLC) demonstrated that RES intra-cellular concentration is increased about 2-fold in cells stably expressing CAV1 or CAVM1 (a scaffolding domain (81-101AA)-defective CAV1 mutant) compared to the untransduced human Hepatoblastoma cell line (HepG2) or after transduction with the green fluorescent protein (GFP) control vector. The increased intra-cellular transport of RES was abolished in cells stably expressing CAVM2 (a cholesterol shuttle domain (143-156AA)-defective CAV1 mutant) or CAVRNAi. In order to further characterize CAV1-dependent RES transport, we synthesized RES-dansyl chloride derivatives as fluorescent probes to visualize the transport process, which demonstrated a distribution consistent with that of CAV1 in HepG2 cells.</p> <p>Results</p> <p>In addition, RES endocytosis was not mediated by estrogen receptor (ER) α and β, as suggested by lack of competitive inhibition by estrogen or Tamoxifen. Pathway analysis showed that RES can up-regulate the expression of endogenous CAV1; this activates further the MAPK pathway and caspase-3 expression.</p> <p>Discussion</p> <p>This study provides novel insights about the role played by CAV1 in modulating cellular sensitivity to RES through enhancement of its internalization and trafficking.</p

New resampling method for evaluating stability of clusters

<p>Abstract</p> <p>Background</p> <p>Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in clustering procedures. Statistical methods are required to distinguish between real and random clusters. Several methods for assessing cluster stability have been published, including resampling methods such as the bootstrap.</p> <p>We propose a new resampling method based on continuous weights to assess the stability of clusters in hierarchical clustering. While in bootstrapping approximately one third of the original items is lost, continuous weights avoid zero elements and instead allow non integer diagonal elements, which leads to retention of the full dimensionality of space, i.e. each variable of the original data set is represented in the resampling sample.</p> <p>Results</p> <p>Comparison of continuous weights and bootstrapping using real datasets and simulation studies reveals the advantage of continuous weights especially when the dataset has only few observations, few differentially expressed genes and the fold change of differentially expressed genes is low.</p> <p>Conclusion</p> <p>We recommend the use of continuous weights in small as well as in large datasets, because according to our results they produce at least the same results as conventional bootstrapping and in some cases they surpass it.</p