Siblings of Crohn's Disease Patients Exhibit a Pathologically Relevant Dysbiosis: Examination of Mucosal Microbiota Communities Using 16S rRNA Gene Pyrosequencing

Background Reduced mucosal concentrations of Faecalibacterium prausnitzii predict disease recurrence in patients with Crohn's disease (CD). Siblings of CD patients have elevated risk of developing CD and share aspects of disease phenotype compared with healthy controls (HC), including dysbiosis in the faecal microbiota.[1] No study has compared the mucosal microbiota of CD siblings with unrelated healthy controls. Aim: to determine whether dysbiosis is present in the mucosal microbiota of siblings of CD patients with reference to HC, and to apply 16S rRNA gene pyrosequencing in order to accomplish a more comprehensive characterisation of that dysbiosis. Methods Rectal biopsies were taken from 21 patients with quiescent CD, 17 of their healthy siblings and 19 unrelated HC. Total DNA was extracted using phenol/chloroform based method. The V1 to V3 region of the bacterial 16S ribosomal RNA gene was amplified using PCR, and microbiota composition resolved by 454 pyrosequencing. Sequence processing and analyses were performed using the open source Mothur software package (www.mothur.org). Results For each group the resulting species in the microbiota were classified into core (common and abundant among similar subjects) versus infrequent and rare.[2] In terms of both microbial diversity (measured by both the ShannonWiener and Simpson's indexes of diversity) and species richness, the core mucosal microbiota of both siblings and CD patients were significantly less diverse than HC. Although the diversity of the rare microbiota was lower in CD compared with HC, there was no difference in diversity of rare microbiota between siblings and HC. Metacommunity profiling using the Bray-Curtis (SBC) index of similarity with unweighted pair group averages showed that the core microbial metacommunity of siblings was more similar to CD (SBC=0.70) than to HC, whereas the rare microbial metacommunity of siblings was more similar to HC (SBC= 0.42). As in CD patients, the species that contributed most to the dissimilarity between healthy siblings and HC was F. prausnitzii, Table 1. Conclusions This is the first in depth case-control study of the mucosal microbiota in the siblings of CD patients. We report a dysbiosis characterised by reduced diversity of core microbiota and lower abundance of F. prausnitzii. Given that siblings of CD patients have elevated risk of developing CD, this dysbiosis in otherwise healthy people implicates microbiological processes in CD pathogenesis and risk

Siblings Of Crohn’s Disease Patients Exhibit A Biologically Relevant Dysbiosis In The Mucosal Microbial Community: A 16s Rrna Gene Pyrosequencing Study

Introduction Reduced mucosal Faecalibacterium prausnitzii predicts disease recurrence in Crohn’s disease (CD) patients. Siblings (SIBS) of CD patients have elevated risk of developing CD and share aspects of CD phenotype including faecal dysbiosis. [1] No study has compared mucosal microbiota in CD SIBS to unrelated healthy controls (HC). Methods Phenol/chloroform DNA extraction from rectal biopsies of 21 patients with quiescent CD, 17 of their healthy SIBS and 19 unrelated HC, and PCR amplification of the V1-V3 region of the bacterial 16S ribosomal RNA gene were performed. Microbiota composition was resolved by 454 pyrosequencing. Results For each group, mucosal microbiota were classified into common/abundant (core) vs. infrequent/rare.2 In terms of both microbial diversity (Shannon-Wiener and Simpson’s indexes of diversity) and species richness, core microbiota of both SIBS and CD patients were significantly less diverse than HC. The rare microbiota diversity was lower in CD compared with HC, but was not different between SIBS and HC. Metacommunity profiling (Bray-Curtis (SBC) index of similarity with unweighted pair group averages) showed core microbial metacommunity of SIBS to be more similar to CD (SBC=0.70) than to HC, whereas the rare microbial metacommunity of SIBS was more similar to HC (SBC=0.42). As in CD patients, the species that contributed most to the dissimilarity of healthy SIBS vs. HC was F. prausnitzii, Table 1. Conclusion This is the first in depth case-control study of the mucosal microbiota of SIBS of CD patients. Dysbiosis in SIBS was characterised by reduced diversity of core microbiota and lower abundance of F. prausnitzii. This dysbiosis in otherwise healthy, but at-risk people implicates microbiological processes in CD pathogenesis and risk

Impact of socioeconomic deprivation on rate and cause of death in severe mental illness

Background: Socioeconomic status has important associations with disease-specific mortality in the general population. Although individuals with Severe Mental Illnesses (SMI) experience significant premature mortality, the relationship between socioeconomic status and mortality in this group remains under investigated.<p></p> Aims: To assess the impact of socioeconomic status on rate and cause of death in individuals with SMI (schizophrenia and bipolar disorder) relative to the local (Glasgow) and wider (Scottish) populations.<p></p> Methods: Cause and age of death during 2006-2010 inclusive for individuals with schizophrenia or bipolar disorder registered on the Glasgow Psychosis Clinical Information System (PsyCIS) were obtained by linkage to the Scottish General Register Office (GRO). Rate and cause of death by socioeconomic status, measured by Scottish Index of Multiple Deprivation (SIMD), were compared to the Glasgow and Scottish populations.<p></p> Results: Death rates were higher in people with SMI across all socioeconomic quintiles compared to the Glasgow and Scottish populations, and persisted when suicide was excluded. Differences were largest in the most deprived quintile (794.6 per 10,000 population vs. 274.7 and 252.4 for Glasgow and Scotland respectively). Cause of death varied by socioeconomic status. For those living in the most deprived quintile, higher drug-related deaths occurred in those with SMI compared to local Glasgow and wider Scottish population rates (12.3% vs. 5.9%, p = <0.001 and 5.1% p = 0.002 respectively). A lower proportion of deaths due to cancer in those with SMI living in the most deprived quintile were also observed, relative to the local Glasgow and wider Scottish populations (12.3% vs. 25.1% p = 0.013 and 26.3% p = <0.001). The proportion of suicides was significantly higher in those with SMI living in the more affluent quintiles relative to Glasgow and Scotland (54.6% vs. 5.8%, p = <0.001 and 5.5%, p = <0.001). Discussion and conclusions: Excess mortality in those with SMI occurred across all socioeconomic quintiles compared to the Glasgow and Scottish populations but was most marked in the most deprived quintiles when suicide was excluded as a cause of death. Further work assessing the impact of socioeconomic status on specific causes of premature mortality in SMI is needed

The Periotest Method: Implant-Supported Framework Precision of Fit Evaluation

: In this study, the Periotest instrument was used to measure the precision of fit between cast high noble-metal frameworks and the supporting implants in a patient-simulation model. Three framework conditions and three implant-location variables were used to evaluate the rigidity of the assembly as measured by the Periotest method. The framework variables were (1) one-piece castings (OPC); (2) sectioned-soldered inaccurate castings (SSIC); and (3) sectioned-soldered accurate castings (SSAC). The implant-location variables were right anterior (RA), center (C), and left anterior (LA). Materials and Methods : The patient simulation model used consisted of three self-tapping BrÅnemark implants in a reasonable arch curvature in bovine bone. Three working casts were fabricated from the patient-simulation model using polyvinyl siloxane and tapered impression copings. From the working casts, three sets of three frameworks were fabricated as OPCs, SSICs, and SSACs using type 3 high noble alloy. The SSICs were fabricated with a quantitative misfit of 101.6 Μm at the facial surface, between the abutment-to-gold cylinder interface at the C implant location. Periotest value (PTV) measurements were made at the midfacial surface of the frameworks directly above each abutment-to-gold cylinder interface. Three measurements were made for each test condition. The data were analyzed to compare framework condition(s) and implant location(s) using ANOVA and Fisher's Protected Least Significant Difference Comparison Test. Results : The ANOVA showed that significant differences exist between the mean PTV data for framework condition and for implant location (p < .01). Significant differences were shown between the mean PTV data for the SSAC assemblies and the OPC and SSIC assemblies. The SSICs displayed a more positive (+) mean PTV than the OPCs. The OPC assemblies had a more positive mean PTV than the SSAC assemblies. The mean PTV data for the SSAC assemblies had a significantly different PTV (p < .01) than the other two framework condition assemblies. The OPC and the SSIC assemblies had PTVs that were not significantly different. The C implant location was significantly different from the RA and the LA implant locations (p < .01). The RA and the LA implant locations were not significantly different from each other. The C implant location always demonstrated the most positive mean PTV regardless of the framework condition being tested. Conclusions : The Periotest instrument quantified differences in the precision of fit between three framework conditions. The SSAC assemblies were significantly more rigid than the OPC and SSIC assemblies. The OPC and SSIC assemblies' mean PTVs were not significantly different. The mean PTVs for the C implant location and the RA and LA implant locations were significantly different (p < .01). The mean PTVs of the RA and LA implant locations were not significantly different. The implant-location PTVs followed the same rank order for all three framework conditions. The procedures used to fabricate a more precise fit between the framework and the supporting implants is influenced by the skill of the clinician and technician.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75096/1/j.1532-849X.1996.tb00298.x.pd

Be SMART:examining the experience of implementing the NHS Health Check in UK primary care

Background: The NHS Health Check was designed by UK Department of Health to address increased prevalence of cardiovascular disease by identifying risk levels and facilitating behaviour change. It constituted biomedical testing, personalised advice and lifestyle support. The objective of the study was to explore Health Care Professionals' (HCPs) and patients' experiences of delivering and receiving the NHS Health Check in an inner-city region of England. Methods: Patients and HCPs in primary care were interviewed using semi-structured schedules. Data were analysed using Thematic Analysis. Results: Four themes were identified. Firstly, Health Check as a test of 'roadworthiness' for people. The roadworthiness metaphor resonated with some patients but it signified a passive stance toward illness. Some patients described the check as useful in the theme, Health check as revelatory. HCPs found visual aids demonstrating levels of salt/fat/sugar in everyday foods and a 'traffic light' tape measure helpful in communicating such 'revelations' with patients. Being SMART and following the protocolrevealed that few HCPs used SMART goals and few patients spoke of them. HCPs require training to understand their rationale compared with traditional advice-giving. The need for further follow-up revealed disparity in follow-ups and patients were not systematically monitored over time. Conclusions: HCPs' training needs to include the use and evidence of the effectiveness of SMART goals in changing health behaviours. The significance of fidelity to protocol needs to be communicated to HCPs and commissioners to ensure consistency. Monitoring and measurement of follow-up, e.g., tracking of referrals, need to be resourced to provide evidence of the success of the NHS Health Check in terms of healthier lifestyles and reduced CVD risk

APP controls the formation of PI(3,5)P2 vesicles through its binding of the PIKfyve complex

Phosphoinositides are signalling lipids that are crucial for major signalling events as well as established regulators of membrane trafficking. Control of endosomal sorting and endosomal homeostasis requires phosphatidylinositol-3-phosphate (PI(3)P) and phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2), the latter a lipid of low abundance but significant physiological relevance. PI(3,5)P2 is formed by phosphorylation of PI(3)P by the PIKfyve complex which is crucial for maintaining endosomal homeostasis. Interestingly, loss of PIKfyve function results in dramatic neurodegeneration. Despite the significance of PIKfyve, its regulation is still poorly understood. Here we show that the Amyloid Precursor Protein (APP), a central molecule in Alzheimer’s disease, associates with the PIKfyve complex (consisting of Vac14, PIKfyve and Fig4) and that the APP intracellular domain directly binds purified Vac14. We also show that the closely related APP paralogues, APLP1 and 2 associate with the PIKfyve complex. Whether APP family proteins can additionally form direct protein–protein interaction with PIKfyve or Fig4 remains to be explored. We show that APP binding to the PIKfyve complex drives formation of PI(3,5)P2 positive vesicles and that APP gene family members are required for supporting PIKfyve function. Interestingly, the PIKfyve complex is required for APP trafficking, suggesting a feedback loop in which APP, by binding to and stimulating PI(3,5)P2 vesicle formation may control its own trafficking. These data suggest that altered APP processing, as observed in Alzheimer’s disease, may disrupt PI(3,5)P2 metabolism, endosomal sorting and homeostasis with important implications for our understanding of the mechanism of neurodegeneration in Alzheimer’s disease

Characterising and Predicting Benthic Biodiversity for Conservation Planning in Deepwater Environments

Understanding patterns of biodiversity in deep sea systems is increasingly important because human activities are extending further into these areas. However, obtaining data is difficult, limiting the ability of science to inform management decisions. We have used three different methods of quantifying biodiversity to describe patterns of biodiversity in an area that includes two marine reserves in deep water off southern Australia. We used biological data collected during a recent survey, combined with extensive physical data to model, predict and map three different attributes of biodiversity: distributions of common species, beta diversity and rank abundance distributions (RAD). The distribution of each of eight common species was unique, although all the species respond to a depth-correlated physical gradient. Changes in composition (beta diversity) were large, even between sites with very similar environmental conditions. Composition at any one site was highly uncertain, and the suite of species changed dramatically both across and down slope. In contrast, the distributions of the RAD components of biodiversity (community abundance, richness, and evenness) were relatively smooth across the study area, suggesting that assemblage structure (i.e. the distribution of abundances of species) is limited, irrespective of species composition. Seamounts had similar biodiversity based on metrics of species presence, beta diversity, total abundance, richness and evenness to the adjacent continental slope in the same depth ranges. These analyses suggest that conservation objectives need to clearly identify which aspects of biodiversity are valued, and employ an appropriate suite of methods to address these aspects, to ensure that conservation goals are met

Quantitative electron phase imaging with high sensitivity and an unlimited field of view

As it passes through a sample, an electron beam scatters, producing an exit wavefront rich in information. A range of material properties, from electric and magnetic field strengths to specimen thickness, strain maps and mean inner potentials, can be extrapolated from its phase and mapped at the nanoscale. Unfortunately, the phase signal is not straightforward to obtain. It is most commonly measured using off-axis electron holography, but this is experimentally challenging, places constraints on the sample and has a limited field of view. Here we report an alternative method that avoids these limitations and is easily implemented on an unmodified transmission electron microscope (TEM) operating in the familiar selected area diffraction mode. We use ptychography, an imaging technique popular amongst the X-ray microscopy community; recent advances in reconstruction algorithms now reveal its potential as a tool for highly sensitive, quantitative electron phase imaging