Identification of the factors associated with outcomes in a condition management programme

<p>Background: A requirement of the Government’s Pathways to Work (PtW) agenda was to introduce a Condition Management Programme (CMP). The aim of the present study was to identify the differences between those who engaged and made progress in this telephone-based biopsychosocial intervention, in terms of their health, and those who did not and to determine the client and practitioner characteristics and programme elements associated with success in a programme aimed at improving health.</p> <p>Methods: Data were obtained from the CMP electronic spreadsheets and clients paper-based case records. CMP standard practice was that questionnaires were administered during the pre- and post-assessment phases over the telephone. Each client’s record contains their socio-demographic data, their primary health condition, as well as the pre- and post-intervention scores of the health assessment tool administered. Univariate and multivariate statistical analysis was used to investigate the relationships between the database variables. Clients were included in the study if their records were available for analysis from July 2006 to December 2007.</p> <p> Results: On average there were 112 referrals per month, totalling 2016 referrals during the evaluation period. The majority (62.8%) of clients had a mental-health condition. Successful completion of the programme was 28.5% (575 “completers”; 144 “discharges”). Several factors, such as age, health condition, mode of contact, and practitioner characteristics, were significant determinants of participation and completion of the programme. The results showed that completion of the CMP was associated with a better mental-health status, by reducing the number of clients that were either anxious, depressed or both, before undertaking the programme, from 74% to 32.5%.</p> <p>Conclusions: Our findings showed that an individual's characteristics are associated with success in the programme, defined as completing the intervention and demonstrating an improved health status. This study provides some evidence that the systematic evaluation of such programmes and interventions could identify ways in which they could be improved.</p&gt

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

Polydrug Use among IDUs in Tijuana, Mexico: Correlates of Methamphetamine Use and Route of Administration by Gender

Tijuana is situated on the Mexico–USA border adjacent to San Diego, CA, on a major drug trafficking route. Increased methamphetamine trafficking in recent years has created a local consumption market. We examined factors associated with methamphetamine use and routes of administration by gender among injection drug users (IDUs). From 2006–2007, IDUs ≥18 years old in Tijuana were recruited using respondent-driven sampling, interviewed, and tested for HIV, syphilis, and TB. Logistic regression was used to assess associations with methamphetamine use (past 6 months), stratified by gender. Among 1,056 participants, methamphetamine use was more commonly reported among females compared to males (80% vs. 68%, p < 0.01), particularly, methamphetamine smoking (57% vs. 34%; p < 0.01). Among females (N = 158), being aged >35 years (AOR, 0.2; 95% CI, 0.1–0.6) was associated with methamphetamine use. Among males (N = 898), being aged >35 years (AOR, 0.5; 95% CI, 0.3–0.6), homeless (AOR, 1.4 (0.9–2.2)), and ever reporting sex with another male (MSM; AOR, 1.9; 95% CI, 1.4–2.7) were associated with methamphetamine use. Among males, a history of MSM was associated with injection, while sex trade and >2 casual sex partners were associated with multiple routes of administration. HIV was higher among both males and females reporting injection as the only route of methamphetamine administration. Methamphetamine use is highly prevalent among IDUs in Tijuana, especially among females. Routes of administration differed by gender and subgroup which has important implications for tailoring harm reduction interventions and drug abuse treatment

HER 2/neu protein expression in colorectal cancer

BACKGROUND: Conflicting data exist about the prevalence of HER-2/neu overexpression in colorectal cancer ranging from 0 to 83 %. In our study we tried to clarify the extent of expression and its relationship to clinicopathological parameters. METHODS: This study involved 77 specimens of malignant colorectal cancer lesions of surgically resected patients. HER-2/neu immunohistochemistry was performed using the Hercep-Test Kit. RESULTS: Out of 77 specimens, 56 were Her-2/neu negative (70%), 20 (26%) showed a barely immunostaining (1+), only 1 (1%) was moderately (2+) and 2 (3%) were strongly positive (3+). Her-2/neu staining (moderately and strongly positive) was only detected in primary tumours of patients with confirmed metastases. No relationship was found between membranous HER-2 expression and patients' gender or differentiation. The median survival time of patients with positive HER-2/neu immunostaining was 21 versus 39 months in patients without HER-2/neu expression (p = 0.088). CONCLUSION: The c-erbB protein expression was observed in colorectal cancer but rarely in the therapeutic range (2+ and 3+). There was no significant association with tumour grade, gender, localization of the primary tumour or survival. These data indicate that c-erbB-2 is unlikely to play a major role in the therapeutic management of colorectal cancer

Diversity and dynamics of rare and of resident bacterial populations in coastal sands

Coastal sands filter and accumulate organic and inorganic materials from the terrestrial and marine environment, and thus provide a high diversity of microbial niches. Sands of temperate climate zones represent a temporally and spatially highly dynamic marine environment characterized by strong physical mixing and seasonal variation. Yet little is known about the temporal fluctuations of resident and rare members of bacterial communities in this environment. By combining community fingerprinting via pyrosequencing of ribosomal genes with the characterization of multiple environmental parameters, we disentangled the effects of seasonality, environmental heterogeneity, sediment depth and biogeochemical gradients on the fluctuations of bacterial communities of marine sands. Surprisingly, only 3–5% of all bacterial types of a given depth zone were present at all times, but 50–80% of them belonged to the most abundant types in the data set. About 60–70% of the bacterial types consisted of tag sequences occurring only once over a period of 1 year. Most members of the rare biosphere did not become abundant at any time or at any sediment depth, but varied significantly with environmental parameters associated with nutritional stress. Despite the large proportion and turnover of rare organisms, the overall community patterns were driven by deterministic relationships associated with seasonal fluctuations in key biogeochemical parameters related to primary productivity. The maintenance of major biogeochemical functions throughout the observation period suggests that the small proportion of resident bacterial types in sands perform the key biogeochemical processes, with minimal effects from the rare fraction of the communities

Influence of nutrients and currents on the genomic composition of microbes across an upwelling mosaic

Metagenomic data sets were generated from samples collected along a coastal to open ocean transect between Southern California Bight and California Current waters during a seasonal upwelling event, providing an opportunity to examine the impact of episodic pulses of cold nutrient-rich water into surface ocean microbial communities. The data set consists of ∼5.8 million predicted proteins across seven sites, from three different size classes: 0.1–0.8, 0.8–3.0 and 3.0–200.0 μm. Taxonomic and metabolic analyses suggest that sequences from the 0.1–0.8 μm size class correlated with their position along the upwelling mosaic. However, taxonomic profiles of bacteria from the larger size classes (0.8–200 μm) were less constrained by habitat and characterized by an increase in Cyanobacteria, Bacteroidetes, Flavobacteria and double-stranded DNA viral sequences. Functional annotation of transmembrane proteins indicate that sites comprised of organisms with small genomes have an enrichment of transporters with substrate specificities for amino acids, iron and cadmium, whereas organisms with larger genomes have a higher percentage of transporters for ammonium and potassium. Eukaryotic-type glutamine synthetase (GS) II proteins were identified and taxonomically classified as viral, most closely related to the GSII in Mimivirus, suggesting that marine Mimivirus-like particles may have played a role in the transfer of GSII gene functions. Additionally, a Planctomycete bloom was sampled from one upwelling site providing a rare opportunity to assess the genomic composition of a marine Planctomycete population. The significant correlations observed between genomic properties, community structure and nutrient availability provide insights into habitat-driven dynamics among oligotrophic versus upwelled marine waters adjoining each other spatially

Defining seasonal marine microbial community dynamics

Here we describe, the longest microbial time-series analyzed to date using high-resolution 16S rRNA tag pyrosequencing of samples taken monthly over 6 years at a temperate marine coastal site off Plymouth, UK. Data treatment effected the estimation of community richness over a 6-year period, whereby 8794 operational taxonomic units (OTUs) were identified using single-linkage preclustering and 21 130 OTUs were identified by denoising the data. The Alphaproteobacteria were the most abundant Class, and the most frequently recorded OTUs were members of the Rickettsiales (SAR 11) and Rhodobacteriales. This near-surface ocean bacterial community showed strong repeatable seasonal patterns, which were defined by winter peaks in diversity across all years. Environmental variables explained far more variation in seasonally predictable bacteria than did data on protists or metazoan biomass. Change in day length alone explains >65% of the variance in community diversity. The results suggested that seasonal changes in environmental variables are more important than trophic interactions. Interestingly, microbial association network analysis showed that correlations in abundance were stronger within bacterial taxa rather than between bacteria and eukaryotes, or between bacteria and environmental variables

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Probing Metagenomics by Rapid Cluster Analysis of Very Large Datasets

BACKGROUND: The scale and diversity of metagenomic sequencing projects challenge both our technical and conceptual approaches in gene and genome annotations. The recent Sorcerer II Global Ocean Sampling (GOS) expedition yielded millions of predicted protein sequences, which significantly altered the landscape of known protein space by more than doubling its size and adding thousands of new families (Yooseph et al., 2007 PLoS Biol 5, e16). Such datasets, not only by their sheer size, but also by many other features, defy conventional analysis and annotation methods. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we describe an approach for rapid analysis of the sequence diversity and the internal structure of such very large datasets by advanced clustering strategies using the newly modified CD-HIT algorithm. We performed a hierarchical clustering analysis on the 17.4 million Open Reading Frames (ORFs) identified from the GOS study and found over 33 thousand large predicted protein clusters comprising nearly 6 million sequences. Twenty percent of these clusters did not match known protein families by sequence similarity search and might represent novel protein families. Distributions of the large clusters were illustrated on organism composition, functional class, and sample locations. CONCLUSION/SIGNIFICANCE: Our clustering took about two orders of magnitude less computational effort than the similar protein family analysis of original GOS study. This approach will help to analyze other large metagenomic datasets in the future. A Web server with our clustering results and annotations of predicted protein clusters is available online at http://tools.camera.calit2.net/gos under the CAMERA project