Disease management for co-morbid depression and anxiety in diabetes mellitus: design of a randomised controlled trial in primary care

BACKGROUND: Depression and anxiety are common co-morbid health problems in patients with type 2 diabetes. Both depression and anxiety are associated with poor glycaemic control and increased risk of poor vascular outcomes and higher mortality rates. Results of previous studies have shown that in clinical practice, treatment of depression and anxiety is far from optimal as these symptoms are frequently overlooked and undertreated. METHODS/DESIGN: This randomised controlled trial will examine the effectiveness of a disease management programme treating symptoms of depression and anxiety in primary care patients with Type 2 diabetes. Patients will be randomized on patient level in 1:1 ratio. Random block sizes of 2 and 4 are used. The disease management programme consists of screening, stepped treatment and monitoring of symptoms (n = 80). This will be compared to care as usual (n = 80). DISCUSSION: The disease management model for co-morbid depression and anxiety in primary care patients with diabetes is expected to result in reduced symptoms of depression and anxiety, improved quality of life, reduced diabetes specific distress and improved glyceamic control, compared to care as usual. TRIAL REGISTRATION: Dutch Trial Register NTR262

Numerical simulation of biofilm formation in a microchannel

The focus of this paper is the numerical solution of a pore-scale model for the growth of a permeable biofilm. The model includes water flux inside the biofilm, different biofilm components, and shear stress on the biofilm-water interface. To solve the resulting highly coupled system of model equations, we propose a splitting algorithm. The Arbitrary Lagrangian Eulerian (ALE) method is used to track the biofilm-water interface. Numerical simulations are performed using physical parameters from the existing literature. Our computations show the effect of biofilm permeability on the nutrient transport and on its growth

Role of pentraxin-3 in risk assessment of patients with metabolic syndrome

Background Inflammation plays a major role in the development of metabolic syndrome (MetS) and its progression. Recent studies have shown that pentraxin-3 (PTX-3), osteoprogerin (OPG), and tumor necrosis factor-alpha (TNF-α) are key factors in MetS pathophysiology, but evidence for endorsing their clinical use is currently unclear and insufficient. Aim The study aimed to evaluate the association between the inflammatory biomarkers’ levels and the severity of MetS. Methods The study was observational, transversal, prospective, cohort, and analytical type. We enrolled 80 patients (M:F = 1, mean age = 55 ± 10.77 years) who met MetS criteria. The study protocol included: medical history, physical examination, 6-min walk test distance (6MWTD), biochemical tests, electrocardiogram, echocardiography, and carotid ultrasonography. We also performed plasmatic measurement of PTX-3, OPG, and TNF-α, in addition to standard biochemical tests. Results Subjects with severe MetS had higher values of body mass index (BMI) and waist circumference (p  Conclusion PTX-3 was correlated with the severity of MetS, with other inflammatory parameters and cardiovascular tests. CCA-IMT and 6MWTD are useful in differentiating between mild and severe MetS

LOCAS – A Low Coverage Assembly Tool for Resequencing Projects

Motivation: Next Generation Sequencing (NGS) is a frequently applied approach to detect sequence variations between highly related genomes. Recent large-scale re-sequencing studies as the Human 1000 Genomes Project utilize NGS data of low coverage to afford sequencing of hundreds of individuals. Here, SNPs and micro-indels can be detected by applying an alignment-consensus approach. However, computational methods capable of discovering other variations such as novel insertions or highly diverged sequence from low coverage NGS data are still lacking. Results: We present LOCAS, a new NGS assembler particularly designed for low coverage assembly of eukaryotic genomes using a mismatch sensitive overlap-layout-consensus approach. LOCAS assembles homologous regions in a homologyguided manner while it performs de novo assemblies of insertions and highly polymorphic target regions subsequently to an alignment-consensus approach. LOCAS has been evaluated in homology-guided assembly scenarios with low sequence coverage of Arabidopsis thaliana strains sequenced as part of the Arabidopsis 1001 Genomes Project. While assembling the same amount of long insertions as state-of-the-art NGS assemblers, LOCAS showed best results regarding contig size, error rate and runtime. Conclusion: LOCAS produces excellent results for homology-guided assembly of eukaryotic genomes with short reads and low sequencing depth, and therefore appears to be the assembly tool of choice for the detection of novel sequenc

Meraculous: De Novo Genome Assembly with Short Paired-End Reads

We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast Pichia stipitis. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by ∼280 bp or ∼3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed

Double trouble at high density::Cross-level test of ressource-related adaptive plasticity and crowding-related fitness.

Population size is often regulated by negative feedback between population density and individual fitness. At high population densities, animals run into double trouble: they might concurrently suffer from overexploitation of resources and also from negative interference among individuals regardless of resource availability, referred to as crowding. Animals are able to adapt to resource shortages by exhibiting a repertoire of life history and physiological plasticities. In addition to resource-related plasticity, crowding might lead to reduced fitness, with consequences for individual life history. We explored how different mechanisms behind resource-related plasticity and crowding-related fitness act independently or together, using the water flea Daphnia magna as a case study. For testing hypotheses related to mechanisms of plasticity and crowding stress across different biological levels, we used an individual-based population model that is based on dynamic energy budget theory. Each of the hypotheses, represented by a sub-model, is based on specific assumptions on how the uptake and allocation of energy are altered under conditions of resource shortage or crowding. For cross-level testing of different hypotheses, we explored how well the sub-models fit individual level data and also how well they predict population dynamics under different conditions of resource availability. Only operating resource-related and crowding-related hypotheses together enabled accurate model predictions of D. magna population dynamics and size structure. Whereas this study showed that various mechanisms might play a role in the negative feedback between population density and individual life history, it also indicated that different density levels might instigate the onset of the different mechanisms. This study provides an example of how the integration of dynamic energy budget theory and individual-based modelling can facilitate the exploration of mechanisms behind the regulation of population size. Such understanding is important for assessment, management and the conservation of populations and thereby biodiversity in ecosystems

Evaluation of the Edinburgh Post Natal Depression Scale using Rasch analysis

BACKGROUND: The Edinburgh Postnatal Depression Scale (EPDS) is a 10 item self-rating post-natal depression scale which has seen widespread use in epidemiological and clinical studies. Concern has been raised over the validity of the EPDS as a single summed scale, with suggestions that it measures two separate aspects, one of depressive feelings, the other of anxiety. METHODS: As part of a larger cross-sectional study conducted in Melbourne, Australia, a community sample (324 women, ranging in age from 18 to 44 years: mean = 32 yrs, SD = 4.6), was obtained by inviting primiparous women to participate voluntarily in this study. Data from the EPDS were fitted to the Rasch measurement model and tested for appropriate category ordering, for item bias through Differential Item Functioning (DIF) analysis, and for unidimensionality through tests of the assumption of local independence. RESULTS: Rasch analysis of the data from the ten item scale initially demonstrated a lack of fit to the model with a significant Item-Trait Interaction total chi-square (chi Square = 82.8, df = 40; p < .001). Removal of two items (items 7 and 8) resulted in a non-significant Item-Trait Interaction total chi-square with a residual mean value for items of -0.467 with a standard deviation of 0.850, showing fit to the model. No DIF existed in the final 8-item scale (EPDS-8) and all items showed fit to model expectations. Principal Components Analysis of the residuals supported the local independence assumption, and unidimensionality of the revised EPDS-8 scale. Revised cut points were identified for EPDS-8 to maintain the case identification of the original scale. CONCLUSION: The results of this study suggest that EPDS, in its original 10 item form, is not a viable scale for the unidimensional measurement of depression. Rasch analysis suggests that a revised eight item version (EPDS-8) would provide a more psychometrically robust scale. The revised cut points of 7/8 and 9/10 for the EPDS-8 show high levels of agreement with the original case identification for the EPDS-10

Superconducting Nanocircuits for Topologically Protected Qubits

For successful realization of a quantum computer, its building blocks (qubits) should be simultaneously scalable and sufficiently protected from environmental noise. Recently, a novel approach to the protection of superconducting qubits has been proposed. The idea is to prevent errors at the "hardware" level, by building a fault-free (topologically protected) logical qubit from "faulty" physical qubits with properly engineered interactions between them. It has been predicted that the decoupling of a protected logical qubit from local noises would grow exponentially with the number of physical qubits. Here we report on the proof-of-concept experiments with a prototype device which consists of twelve physical qubits made of nanoscale Josephson junctions. We observed that due to properly tuned quantum fluctuations, this qubit is protected against magnetic flux variations well beyond linear order, in agreement with theoretical predictions. These results demonstrate the feasibility of topologically protected superconducting qubits.Comment: 25 pages, 5 figure

Global Transcriptional Programs in Peripheral Nerve Endoneurium and DRG Are Resistant to the Onset of Type 1 Diabetic Neuropathy in Ins2Akita/+ Mice

While the morphological and electrophysiological changes underlying diabetic peripheral neuropathy (DPN) are relatively well described, the involved molecular mechanisms remain poorly understood. In this study, we investigated whether phenotypic changes associated with early DPN are correlated with transcriptional alterations in the neuronal (dorsal root ganglia [DRG]) or the glial (endoneurium) compartments of the peripheral nerve. We used Ins2Akita/+ mice to study transcriptional changes underlying the onset of DPN in type 1 diabetes mellitus (DM). Weight, blood glucose and motor nerve conduction velocity (MNCV) were measured in Ins2Akita/+ and control mice during the first three months of life in order to determine the onset of DPN. Based on this phenotypic characterization, we performed gene expression profiling using sciatic nerve endoneurium and DRG isolated from pre-symptomatic and early symptomatic Ins2Akita/+ mice and sex-matched littermate controls. Our phenotypic analysis of Ins2Akita/+ mice revealed that DPN, as measured by reduced MNCV, is detectable in affected animals already one week after the onset of hyperglycemia. Surprisingly, the onset of DPN was not associated with any major persistent changes in gene expression profiles in either sciatic nerve endoneurium or DRG. Our data thus demonstrated that the transcriptional programs in both endoneurial and neuronal compartments of the peripheral nerve are relatively resistant to the onset of hyperglycemia and hypoinsulinemia suggesting that either minor transcriptional alterations or changes on the proteomic level are responsible for the functional deficits associated with the onset of DPN in type 1 DM