Irritable Bowel Syndrome patients exhibit depressive and anxiety scores in the subsyndromal range

Irritable bowel syndrome (IBS) patients frequently experience affective disorders and psychiatric outpatients frequently meet criteria for IBS. The exact nature of this co-morbidity is not clear. 34 patients with Rome-II diagnosed IBS were recruited from a Gastroenterology clinic. Patients with social anxiety disorder (10 SSRI-remitted and 7 untreated subjects) were used as a psychiatric comparison, 28 normal subjects from our register were included as a fourth group (Volunteers). Depressive and anxiety symptoms were measured by the Beck Depression Inventory (BDI) and Spielberger Trait Anxiety Inventory (STAI), respectively. Personality traits were measured with the Swedish universities Scales of Personality (SSP). IBS subjects had BDI and STAI scores intermediate between those of volunteers and patients, despite their lack of a co-morbid psychiatric diagnosis. A principle component factor analysis of the SSP dataset corresponded closely to the solution published with other samples. ANOVA revealed significant between-group differences for 7 of the 13 SSP variables

The use of randomisation-based efficacy estimators in non-inferiority trials

Background In a non-inferiority (NI) trial, analysis based on the intention-to-treat (ITT) principle is anti-conservative, so current guidelines recommend analysing on a per-protocol (PP) population in addition. However, PP analysis relies on the often implausible assumption of no confounders. Randomisation-based efficacy estimators (RBEEs) allow for treatment non-adherence while maintaining a comparison of randomised groups. Fischer et al. have developed an approach for estimating RBEEs in randomised trials with two active treatments, a common feature of NI trials. The aim of this paper was to demonstrate the use of RBEEs in NI trials using this approach, and to appraise the feasibility of these estimators as the primary analysis in NI trials. Methods Two NI trials were used. One comparing two different dosing regimens for the maintenance of remission in people with ulcerative colitis (CODA), and the other comparing an orally administered treatment to an intravenously administered treatment in preventing skeletal-related events in patients with bone metastases from breast cancer (ZICE). Variables that predicted adherence in each of the trial arms, and were also independent of outcome, were sought in each of the studies. Structural mean models (SMMs) were fitted that conditioned on these variables, and the point estimates and confidence intervals compared to that found in the corresponding ITT and PP analyses. Results In the CODA study, no variables were found that differentially predicted treatment adherence while remaining independent of outcome. The SMM, using standard methodology, moved the point estimate closer to 0 (no difference between arms) compared to the ITT and PP analyses, but the confidence interval was still within the NI margin, indicating that the conclusions drawn would remain the same. In the ZICE study, cognitive functioning as measured by the corresponding domain of the QLQ-C30, and use of chemotherapy at baseline were both differentially associated with adherence while remaining independent of outcome. However, while the SMM again moved the point estimate closer to 0, the confidence interval was wide, overlapping with any NI margin that could be justified. Conclusion Deriving RBEEs in NI trials with two active treatments can provide a randomisation-respecting estimate of treatment efficacy that accounts for treatment adherence, is straightforward to implement, but requires thorough planning during the design stage of the study to ensure that strong baseline predictors of treatment are captured. Extension of the approach to handle nonlinear outcome variables is also required. Trial registration The CODA study: ClinicalTrials.gov, identifier: NCT00708656. Registered on 8 April 2008. The ZICE study trial: ClinicalTrials.gov, identifier: NCT00326820. Registered on 16 May 2006

DL_MG : A Parallel Multigrid Poisson and Poisson–Boltzmann Solver for Electronic Structure Calculations in Vacuum and Solution

The solution of the Poisson equation is a crucial step in electronic structure calculations, yielding the electrostatic potential—a key component of the quantum mechanical Hamiltonian. In recent decades, theoretical advances and increases in computer performance have made it possible to simulate the electronic structure of extended systems in complex environments. This requires the solution of more complicated variants of the Poisson equation, featuring nonhomogeneous dielectric permittivities, ionic concentrations with nonlinear dependencies, and diverse boundary conditions. The analytic solutions generally used to solve the Poisson equation in vacuum (or with homogeneous permittivity) are not applicable in these circumstances, and numerical methods must be used. In this work, we present DL_MG, a flexible, scalable, and accurate solver library, developed specifically to tackle the challenges of solving the Poisson equation in modern large-scale electronic structure calculations on parallel computers. Our solver is based on the multigrid approach and uses an iterative high-order defect correction method to improve the accuracy of solutions. Using two chemically relevant model systems, we tested the accuracy and computational performance of DL_MG when solving the generalized Poisson and Poisson–Boltzmann equations, demonstrating excellent agreement with analytic solutions and efficient scaling to ∼10^9 unknowns and 100s of CPU cores. We also applied DL_MG in actual large-scale electronic structure calculations, using the ONETEP linear-scaling electronic structure package to study a 2615 atom protein–ligand complex with routinely available computational resources. In these calculations, the overall execution time with DL_MG was not significantly greater than the time required for calculations using a conventional FFT-based solver

Using Volatile Organic Compounds to Investigate the Effect of Oral Iron Supplementation on the Human Intestinal Metabolome

Patients with iron deficiency anaemia are treated with oral iron supplementation, which is known to cause gastrointestinal side effects by likely interacting with the gut microbiome. To better study this impact on the microbiome, we investigated oral iron-driven changes in volatile organic compounds (VOCs) in the faecal metabolome. Stool samples from patients with iron deficiency anaemia were collected pre- and post-treatment (n = 45 and 32, respectively). Faecal headspace gas analysis was performed by gas chromatography–mass spectrometry and the changes in VOCs determined. We found that the abundance of short-chain fatty acids and esters fell, while aldehydes increased, after treatment. These changes in pre- vs. post-iron VOCs resemble those reported when the gut is inflamed. Our study shows that iron changes the intestinal metabolome, we suggest by altering the structure of the gut microbial community

Faecal and urine metabolites, but not gut microbiota, may predict response to low FODMAP diet in irritable bowel syndrome

BackgroundThe low FODMAP diet (LFD) leads to clinical response in 50%-80% of patients with irritable bowel syndrome (IBS). It is unclear why only some patients respond.AimsTo determine if differences in baseline faecal microbiota or faecal and urine metabolite profiles may separate clinical responders to the diet from non-responders allowing predictive algorithms to be proposed.MethodsWe recruited adults fulfilling Rome III criteria for IBS to a blinded randomised controlled trial. Patients were randomised to sham diet with a placebo supplement (control) or LFD supplemented with either placebo (LFD) or 1.8 g/d B-galactooligosaccharide (LFD/B-GOS), for 4 weeks. Clinical response was defined as adequate symptom relief at 4 weeks after the intervention (global symptom question). Differences between responders and non-responders in faecal microbiota (FISH, 16S rRNA sequencing) and faecal (gas-liquid chromatography, gas-chromatography mass-spectrometry) and urine (1 H NMR) metabolites were analysed.ResultsAt 4 weeks, clinical response differed across the 3groups with adequate symptom relief of 30% (7/23) in controls, 50% (11/22) in the LFD group and 67% (16/24) in the LFD/B-GOS group (p = 0.048). In the control and the LFD/B-GOS groups, microbiota and metabolites did not separate responders from non-responders. In the LFD group, higher baseline faecal propionate (sensitivity 91%, specificity 89%) and cyclohexanecarboxylic acid esters (sensitivity 80%, specificity 78%), and urine metabolite profile (Q2 0.296 vs. randomised -0.175) predicted clinical response.ConclusionsBaseline faecal and urine metabolites may predict response to the LFD

Optimisation of Urine Sample Preparation for Headspace-Solid Phase Microextraction Gas Chromatography-Mass Spectrometry: Altering Sample pH, Sulphuric Acid Concentration and Phase Ratio

Headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) can be used to measure volatile organic compounds (VOCs) in human urine. However, there is no widely adopted standardised protocol for the preparation of urine samples for analysis resulting in an inability to compare studies reliably between laboratories. This paper investigated the effect of altering urine sample pH, volume, and vial size for optimising detection of VOCs when using HS-SPME-GC-MS. This is the first, direct comparison of H2SO4, HCl, and NaOH as treatment techniques prior to HS-SPME-GC-MS analysis. Altering urine sample pH indicates that H2SO4 is more effective at optimising detection of VOCs than HCl or NaOH. H2SO4 resulted in a significantly larger mean number of VOCs being identified per sample (on average, 33.5 VOCs to 24.3 in HCl or 12.2 in NaOH treated urine) and more unique VOCs, produced a more diverse range of classes of VOCs, and led to less HS-SPME-GC-MS degradation. We propose that adding 0.2 mL of 2.5 M H2SO4 to 1 mL of urine within a 10 mL headspace vial is the optimal sample preparation prior to HS-SPME-GC-MS analysis. We hope the use of our optimised method for urinary HS-SPME-GC-MS analysis will enhance our understanding of human disease and bolster metabolic biomarker identification

Depression, anxiety, and loneliness among adolescents and young adults with IBD in the UK: The role of disease severity, age of onset, and embarrassment of the condition

Purpose: Adolescents and young adults (AYA) with Inflammatory Bowel Disease (IBD) report higher depressive symptoms and anxiety compared to healthy controls, with disease severity and abdominal pain being important factors. In the current study, building on what young people had told us in our previous work, we examined whether embarrassment of the condition, social self-efficacy, and friendship quality mediated the relationship between abdominal pain and disease severity, and mental health/well-being. We also included loneliness as a component of well-being. Methods: Data on depression, anxiety, loneliness, friendship quality, social self-efficacy, and disease embarrassment were collected from 130 AYA with IBD ages 14–25years; data on disease severity and abdominal pain were taken from their medical records. Structural Equation Modeling (SEM) was used to test the relationships between the variables. Results: Using SEM, we established that higher IBD disease activity negatively impacted how AYA felt about their friendships and how embarrassed they were about their condition; embarrassment then influenced reports of mental health, including loneliness. Abdominal pain, disease onset, and social self-efficacy directly predicted internalising problems. Conclusion: In this sample of 14–25-year-old patients with IBD, specifics about the disease (severity and pain) predicted poorer mental health, suggesting discussion of mental health should be part of the clinical dialogue between patient and consultant. In addition, embarrassment about their condition increased depression, anxiety, and loneliness, mediating the relationship between disease severity and well-being. Thus, it is important to consider how perceived stigma affects those with chronic illness, and those issues should be explored in clinic