To what extent does severity of loneliness vary among different mental health diagnostic groups: A cross-sectional study.

Loneliness is a common and debilitating problem in individuals with mental health disorders. However, our knowledge on severity of loneliness in different mental health diagnostic groups and factors associated with loneliness is poor, thus limiting the ability to target and improve loneliness interventions. The current study investigated the association between diagnoses and loneliness and explored whether psychological and social factors were related to loneliness. This study employed a cross-sectional design using data from a completed study which developed a measure of social inclusion. It included 192 participants from secondary, specialist mental health services with a primary diagnosis of psychotic disorders (n = 106), common mental disorders (n = 49), or personality disorders (n = 37). The study explored differences in loneliness between these broad diagnostic groups, and the relationship to loneliness of: affective symptoms, social isolation, perceived discrimination, and internalized stigma. The study adhered to the STROBE checklist for observational research. People with common mental disorders (MD = 3.94, CI = 2.15 to 5.72, P < 0.001) and people with personality disorders (MD = 4.96, CI = 2.88 to 7.05, P < 0.001) reported higher levels of loneliness compared to people with psychosis. These differences remained significant after adjustment for all psychological and social variables. Perceived discrimination and internalized stigma were also independently associated with loneliness and substantially contributed to a final explanatory model. The severity of loneliness varies between different mental health diagnostic groups. Both people with common mental disorders and personality disorders reported higher levels of loneliness than people with psychosis. Addressing perceived mental health discrimination and stigma may help to reduce loneliness

A wavefunction model to chemical bonding

In this paper we give a brief survey on some specific aspects of a wavefunction model for chemical bonding which are connected to or have been motivated in part by the work of the late Istvan Mayer and colleagues. After a brief description of the early wavefunction models as reflected in Mayer's works, naturally leading to electron densities, we discuss localized molecular orbitals, and summarize some of the early initiatives and applications. The concept of the Chemical Hamiltonian, as introduced by Mayer, its extensions and some classical and some more advanced connections will be discussed. The twofold motivating role of Mayer in the development of the earliest, ab initio level macromolecular linear scaling methods, giving proven "ab initio quality" protein energy results by the adjustable density matrix assembler method, and in some other molecular fragment advances will be also pointed out

Validity, reliability, acceptability, and utility of the Social Inclusion Questionnaire User Experience (SInQUE): a clinical tool to facilitate social inclusion amongst people with severe mental health problems.

BACKGROUND: Individuals with severe mental health problems are at risk of social exclusion, which may complicate their recovery. Mental health and social care staff have, until now, had no valid or reliable way of assessing their clients' social inclusion. The Social Inclusion Questionnaire User Experience (SInQUE) was developed to address this. It assesses five domains: social integration; productivity; consumption; access to services; and political engagement, in the year prior to first psychiatric admission (T1) and the year prior to interview (T2) from which a total score at each time point can be calculated. AIMS: To establish the validity, reliability, and acceptability of the SInQUE in individuals with a broad range of psychiatric diagnoses receiving care from community mental health services and its utility for mental health staff. METHOD: Participants were 192 mental health service users with psychosis, personality disorder, or common mental disorder (e.g., depression, anxiety) who completed the SInQUE alongside other validated outcome measures. Test-retest reliability was assessed in a sub-sample of 30 participants and inter-rater reliability was assessed in 11 participants. SInQUE ratings of 28 participants were compared with those of a sibling with no experience of mental illness to account for shared socio-cultural factors. Acceptability and utility of the tool were assessed using completion rates and focus groups with staff. RESULTS: The SInQUE demonstrated acceptable convergent validity. The total score and the Social Integration domain score were strongly correlated with quality of life, both in the full sample and in the three diagnostic groups. Discriminant validity and test-retest reliability were established across all domains, although the test-retest reliability on scores for the Service Access and Political Engagement domains prior to first admission to hospital (T1) was lower than other domains. Inter-rater reliability was excellent for all domains at T1 and T2. CONCLUSIONS: The component of the SInQUE that assesses current social inclusion has good psychometric properties and can be recommended for use by mental health staff

A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis

<p>Abstract</p> <p>Background</p> <p>The success achieved by genome-wide association (GWA) studies in the identification of candidate loci for complex diseases has been accompanied by an inability to explain the bulk of heritability. Here, we describe the algorithm V-Bay, a variational Bayes algorithm for multiple locus GWA analysis, which is designed to identify weaker associations that may contribute to this missing heritability.</p> <p>Results</p> <p>V-Bay provides a novel solution to the computational scaling constraints of most multiple locus methods and can complete a simultaneous analysis of a million genetic markers in a few hours, when using a desktop. Using a range of simulated genetic and GWA experimental scenarios, we demonstrate that V-Bay is highly accurate, and reliably identifies associations that are too weak to be discovered by single-marker testing approaches. V-Bay can also outperform a multiple locus analysis method based on the lasso, which has similar scaling properties for large numbers of genetic markers. For demonstration purposes, we also use V-Bay to confirm associations with gene expression in cell lines derived from the Phase II individuals of HapMap.</p> <p>Conclusions</p> <p>V-Bay is a versatile, fast, and accurate multiple locus GWA analysis tool for the practitioner interested in identifying weaker associations without high false positive rates.</p

Mouse obesity network reconstruction with a variational Bayes algorithm to employ aggressive false positive control

<p>Abstract</p> <p>Background</p> <p>We propose a novel variational Bayes network reconstruction algorithm to extract the most relevant disease factors from high-throughput genomic data-sets. Our algorithm is the only scalable method for regularized network recovery that employs Bayesian model averaging and that can internally estimate an appropriate level of sparsity to ensure few false positives enter the model without the need for cross-validation or a model selection criterion. We use our algorithm to characterize the effect of genetic markers and liver gene expression traits on mouse obesity related phenotypes, including weight, cholesterol, glucose, and free fatty acid levels, in an experiment previously used for discovery and validation of network connections: an F2 intercross between the C57BL/6 J and C3H/HeJ mouse strains, where apolipoprotein E is null on the background.</p> <p>Results</p> <p>We identified eleven genes, Gch1, Zfp69, Dlgap1, Gna14, Yy1, Gabarapl1, Folr2, Fdft1, Cnr2, Slc24a3, and Ccl19, and a quantitative trait locus directly connected to weight, glucose, cholesterol, or free fatty acid levels in our network. None of these genes were identified by other network analyses of this mouse intercross data-set, but all have been previously associated with obesity or related pathologies in independent studies. In addition, through both simulations and data analysis we demonstrate that our algorithm achieves superior performance in terms of power and type I error control than other network recovery algorithms that use the lasso and have bounds on type I error control.</p> <p>Conclusions</p> <p>Our final network contains 118 previously associated and novel genes affecting weight, cholesterol, glucose, and free fatty acid levels that are excellent obesity risk candidates.</p

Coordinated evolution of co-expressed gene clusters in the Drosophila transcriptome

Abstract Background Co-expression of genes that physically cluster together is a common characteristic of eukaryotic transcriptomes. This organization of transcriptomes suggests that coordinated evolution of gene expression for clustered genes may also be common. Clusters where expression evolution of each gene is not independent of their neighbors are important units for understanding transcriptome evolution. Results We used a common microarray platform to measure gene expression in seven closely related species in the Drosophila melanogaster subgroup, accounting for confounding effects of sequence divergence. To summarize the correlation structure among genes in a chromosomal region, we analyzed the fraction of variation along the first principal component of the correlation matrix. We analyzed the correlation for blocks of consecutive genes to assess patterns of correlation that may be manifest at different scales of coordinated expression. We find that expression of physically clustered genes does evolve in a coordinated manner in many locations throughout the genome. Our analysis shows that relatively few of these clusters are near heterochromatin regions and that these clusters tend to be over-dispersed relative to the rest of the genome. This suggests that these clusters are not the byproduct of local gene clustering. We also analyzed the pattern of co-expression among neighboring genes within a single Drosophila species: D. simulans. For the co-expression clusters identified within this species, we find an under-representation of genes displaying a signature of recurrent adaptive amino acid evolution consistent with previous findings. However, clusters displaying co-evolution of expression among species are enriched for adaptively evolving genes. This finding points to a tie between adaptive sequence evolution and evolution of the transcriptome. Conclusion Our results demonstrate that co-evolution of expression in gene clusters is relatively common among species in the D. melanogaster subgroup. We consider the possibility that local regulation of expression in gene clusters may drive the connection between adaptive sequence and coordinated gene expression evolution

A Central Partition of Molecular Conformational Space.III. Combinatorial Determination of the Volume Spanned by a Molecular System

In the first work of this series [physics/0204035] it was shown that the conformational space of a molecule could be described to a fair degree of accuracy by means of a central hyperplane arrangement. The hyperplanes divide the espace into a hierarchical set of cells that can be encoded by the face lattice poset of the arrangement. The model however, lacked explicit rotational symmetry which made impossible to distinguish rotated structures in conformational space. This problem was solved in a second work [physics/0404052] by sorting the elementary 3D components of the molecular system into a set of morphological classes that can be properly oriented in a standard 3D reference frame. This also made possible to find a solution to the problem that is being adressed in the present work: for a molecular system immersed in a heat bath we want to enumerate the subset of cells in conformational space that are visited by the molecule in its thermal wandering. If each visited cell is a vertex on a graph with edges to the adjacent cells, here it is explained how such graph can be built

Impact of homicide by a psychiatric patient on forensic psychiatrists: national survey

Aims and method To explore the experiences and support needs of consultant forensic psychiatrists, whose patients had committed homicide while under their care. We circulated a survey to all forensic psychiatrists in the UK, through the Royal College of Psychiatrists, asking about their experiences of a homicide by a patient under their care. Respondents were invited to discuss their experiences further in a structured telephone interview and themes were identified from these discussions. Data were analysed quantitatively and qualitatively. Results One-third of the 86 respondents had had at least one patient who had committed a homicide while under their care. Of these, over three-quarters (78%) reported that the homicide had a significant impact on their personal life, professional life and/or mental/physical health. For some respondents, the impact was severe and long term. Respondents generally felt that they would have been helped by receiving more support in the aftermath of the homicide. Clinical implications Greater recognition is needed of the impact on treating psychiatrists of homicide by a patient and more support is needed for affected clinicians. Further research is necessary, including the effects of such events on colleagues in other specialties and examination of the costs versus the benefits of mandatory inquiries after homicides

Embedding and characterization of quantum chemical reaction graphs on two-dimensional orientable surfaces

Quantum chemical reaction graphs defined on multidimensional potential energy hypersurfaces are embedded on two-dimensional orientable surfaces. Topological invariants of these graphs and those of the embedding two-dimensional surfaces can characterize various families of chemical reactions. Several examples are given for embeddings of reaction graphs of chemical conformational processes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27383/1/0000413.pd

Nonstatistical dynamics on potentials exhibiting reaction path bifurcations and valley-ridge inflection points

We study reaction dynamics on a model potential energy surface exhibiting post-transition state bifurcation in the vicinity of a valley ridge inflection point. We compute fractional yields of products reached after the VRI region is traversed, both with and without dissipation. It is found that apparently minor variations in the potential lead to significant changes in the reaction dynamics. Moreover, when dissipative effects are incorporated, the product ratio depends in a complicated and highly non-monotonic fashion on the dissipation parameter. Dynamics in the vicinity of the VRI point itself play essentially no role in determining the product ratio, except in the highly dissipative regime.Comment: 33 pages, 10 figures, corrected the author name in reference [6