Werner state structure and entanglement classification

We present applications of the representation theory of Lie groups to the analysis of structure and local unitary classification of Werner states, sometimes called the {\em decoherence-free} states, which are states of $n$ quantum bits left unchanged by local transformations that are the same on each particle. We introduce a multiqubit generalization of the singlet state, and a construction that assembles these into Werner states.Comment: 9 pages, 2 figures, minor changes and corrections for version

Comparison of depression and anxiety symptom networks in reporters and non-reporters of lifetime trauma in two samples of differing severity

Background: Reported trauma is associated with differences in the course and outcomes of depression and anxiety. However, no research has explored the association between reported trauma and patterns of clinically relevant symptoms of both depression and anxiety. Methods: We used network analysis to investigate associations between reported trauma and depression and anxiety symptom interactions in affected individuals from the Genetic Links to Anxiety and Depression (GLAD) Study (n = 17720), and population volunteers from the UK Biobank (n = 11120). Participants with current moderate symptoms of depression or anxiety were grouped into reporters and non-reporters of lifetime trauma. Networks of 16 depression and anxiety symptoms in the two groups were compared using the network comparison test. Results: In the GLAD Study, networks of reporters and non-reporters of lifetime trauma did not differ on any metric. In the UK Biobank, the symptom network of reporters had significantly greater density (7.80) than the network of non-reporters (7.05). Limitations: The data collected in the GLAD Study and the UK Biobank are self-reported with validated or semi-validated questionnaires. Conclusions: Reported lifetime trauma was associated with stronger interactions between symptoms of depression and anxiety in population volunteers. Differences between reporters and non-reporters may not be observed in individuals with severe depression and/or anxiety due to limited variance in the presentation of disorder

Factors associated with anxiety disorder comorbidity

Background Anxiety and depressive disorders often co-occur and the order of their emergence may be associated with different clinical outcomes. However, minimal research has been conducted on anxiety-anxiety comorbidity. This study examined factors associated with anxiety comorbidity and anxiety-MDD temporal sequence. Methods Online, self-report data were collected from the UK-based GLAD and COPING NBR cohorts (N = 38,775). Logistic regression analyses compared differences in sociodemographic, trauma, and clinical factors between single anxiety, anxiety-anxiety comorbidity, anxiety-MDD (major depressive disorder) comorbidity, and MDD-only. Additionally, anxiety-first and MDD-first anxiety-MDD were compared. Differences in familial risk were assessed in those participants with self-reported family history or genotype data. Results Anxiety-anxiety and anxiety-MDD had higher rates of self-reported anxiety or depressive disorder diagnoses, younger age of onset, and higher recurrence than single anxiety. Anxiety-MDD displayed greater clinical severity/complexity than MDD only. Anxiety-anxiety had more severe current anxiety symptoms, less severe current depressive symptoms, and reduced likelihood of self-reporting an anxiety/depressive disorder diagnosis than anxiety-MDD. Anxiety-first anxiety-MDD had a younger age of onset, more severe anxiety symptoms, and less likelihood of self-reporting a diagnosis than MDD-first. Minimal differences in familial risk were found. Limitations Self-report, retrospective measures may introduce recall bias. The familial risk analyses were likely underpowered. Conclusions Anxiety-anxiety comorbidity displayed a similarly severe and complex profile of symptoms as anxiety-MDD but distinct features. For anxiety-MDD, first-onset anxiety had an earlier age of onset and greater severity than MDD-first. Anxiety disorders and comorbidity warrant further investigation and attention in research and practice

Patient characteristics associated with retrospectively self-reported treatment outcomes following psychological therapy for anxiety or depressive disorders - a cohort of GLAD study participants

Background: Progress towards stratified care for anxiety and depression will require the identification of new predictors. We collected data on retrospectively self-reported therapeutic outcomes in adults who received psychological therapy in the UK in the past ten years. We aimed to replicate factors associated with traditional treatment outcome measures from the literature. Methods: Participants were from the Genetic Links to Anxiety and Depression (GLAD) Study, a UK-based volunteer cohort study. We investigated associations between retrospectively self-reported outcomes following therapy, on a five-point scale (global rating of change; GRC) and a range of sociodemographic, clinical and therapy-related factors, using ordinal logistic regression models (n = 2890). Results: Four factors were associated with therapy outcomes (adjusted odds ratios, OR). One sociodemographic factor, having university-level education, was associated with favourable outcomes (OR = 1.37, 95%CI: 1.18, 1.59). Two clinical factors, greater number of reported episodes of illness (OR = 0.95, 95%CI: 0.92, 0.97) and higher levels of personality disorder symptoms (OR = 0.89, 95%CI: 0.87, 0.91), were associated with less favourable outcomes. Finally, reported regular use of additional therapeutic activities was associated with favourable outcomes (OR = 1.39, 95%CI: 1.19, 1.63). There were no statistically significant differences between fully adjusted multivariable and unadjusted univariable odds ratios. Conclusion: Therapy outcome data can be collected quickly and inexpensively using retrospectively self-reported measures in large observational cohorts. Retrospectively self-reported therapy outcomes were associated with four factors previously reported in the literature. Similar data collected in larger observational cohorts may enable detection of novel associations with therapy outcomes, to generate new hypotheses, which can be followed up in prospective studies

Impact of Diaspora: A Study of the Rohingya and Palestinians

Our research will examine the question: How do Palestinian and Rohingya refugees effect on their environment and the environmental impacts associated with displacement? We will qualify the environment in social, economic, and natural contexts. More specifically, we will focus on the Rohingya population in coastal Bangladesh and the Palestinian population in West Bank. Our motivation for this project is to better understand how refugee populations can exist through crises and how they impact the environment and cultures around them. We chose to do a comparative study of these two refugee crises because the Israeli-Palestinian conflict has lasted generations and the exacerbation of the Rohingya displacement is a relative recent development. The importance of this research is relevant as climate change and political climates continue to displace people and the need for systemic and sustainable solutions arises. By looking at the disparity between the effect refugee camps have on their environment and comparing this to the impact the social, economic, and natural environment has on refugees, we will be able to gain insights on the sustainability of refugee camps

Patient characteristics associated with retrospectively self-reported treatment outcomes following psychological therapy for anxiety or depressive disorders - a cohort of GLAD study participants.

Funder: Wellcome TrustFunder: Medical Research CouncilBACKGROUND: Progress towards stratified care for anxiety and depression will require the identification of new predictors. We collected data on retrospectively self-reported therapeutic outcomes in adults who received psychological therapy in the UK in the past ten years. We aimed to replicate factors associated with traditional treatment outcome measures from the literature. METHODS: Participants were from the Genetic Links to Anxiety and Depression (GLAD) Study, a UK-based volunteer cohort study. We investigated associations between retrospectively self-reported outcomes following therapy, on a five-point scale (global rating of change; GRC) and a range of sociodemographic, clinical and therapy-related factors, using ordinal logistic regression models (n = 2890). RESULTS: Four factors were associated with therapy outcomes (adjusted odds ratios, OR). One sociodemographic factor, having university-level education, was associated with favourable outcomes (OR = 1.37, 95%CI: 1.18, 1.59). Two clinical factors, greater number of reported episodes of illness (OR = 0.95, 95%CI: 0.92, 0.97) and higher levels of personality disorder symptoms (OR = 0.89, 95%CI: 0.87, 0.91), were associated with less favourable outcomes. Finally, reported regular use of additional therapeutic activities was associated with favourable outcomes (OR = 1.39, 95%CI: 1.19, 1.63). There were no statistically significant differences between fully adjusted multivariable and unadjusted univariable odds ratios. CONCLUSION: Therapy outcome data can be collected quickly and inexpensively using retrospectively self-reported measures in large observational cohorts. Retrospectively self-reported therapy outcomes were associated with four factors previously reported in the literature. Similar data collected in larger observational cohorts may enable detection of novel associations with therapy outcomes, to generate new hypotheses, which can be followed up in prospective studies

Comparison of symptom-based versus self-reported diagnostic measures of anxiety and depression disorders in the GLAD and COPING cohorts

Background Understanding and improving outcomes for people with anxiety or depression often requires large sample sizes. To increase participation and reduce costs, such research is typically unable to utilise “gold-standard” methods to ascertain diagnoses, instead relying on remote, self-report measures. Aims Assess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research. Method Participants from the UK-based GLAD and COPING NBR cohorts (N = 58,400) completed an online questionnaire between 2018 and 2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate symptom-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed self-reported diagnoses. “Any anxiety” included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohen’s kappa, McNemar’s chi-squared, sensitivity, and specificity. Results Agreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with self-reported GAD did not receive a symptom-based diagnosis. In contrast, symptom-based diagnoses of the phobic disorders were more common than self-reported diagnoses. Conclusions Agreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, self-reported diagnoses classified most participants as having GAD, whereas symptom-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required

Genomic reconstruction of the SARS-CoV-2 epidemic in England

AbstractThe evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.</jats:p