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Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.
Methods
We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.
Results
The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).
Conclusion
The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.
Background: Efgartigimod, a human immunoglobulin G (IgG)1 antibody Fc fragment, blocks the neonatal Fc receptor, decreasing IgG recycling and reducing pathogenic IgG autoantibody levels. ADHERE assessed the efficacy and safety of efgartigimod PH20 subcutaneous (SC; co-formulated with recombinant human hyaluronidase PH20) in chronic inflammatory demyelinating polyneuropathy (CIDP). Methods: ADHERE enrolled participants with CIDP (treatment naive or on standard treatments withdrawn during run-in period) and consisted of open-label Stage A (efgartigimod PH20 SC once weekly [QW]), and randomized (1:1) Stage B (efgartigimod or placebo QW). Primary outcomes were clinical improvement (assessed with aINCAT, I-RODS, or mean grip strength; Stage A) and time to first aINCAT score deterioration (relapse; Stage B). Secondary outcomes included treatment-emergent adverse events (TEAEs) incidence. Results: 322 participants entered Stage A. 214 (66.5%) were considered responders, randomized, and treated in Stage B. Efgartigimod significantly reduced the risk of relapse (HR: 0.394; 95% CI: 0.25–0.61) versus placebo (p=0.000039). Reduced risk of relapse occurred in participants receiving corticosteroids, intravenous or SC immunoglobulin, or no treatment before study entry. Most TEAEs were mild to moderate; 3 deaths occurred, none related to efgartigimod. Conclusions: Participants treated with efgartigimod PH20 SC maintained a clinical response and remained relapse-free longer than those treated with placebo.
Mangroves, tidal marshes and seagrasses have experienced extensive historical reduction in extent due to direct and indirect effects of anthropogenic land use change. Habitat loss has contributed carbon emissions and led to foregone opportunities for carbon sequestration, which are disproportionately large due to high ‘blue carbon’ stocks and sequestration rates in these coastal ecosystems. As such, there has been a rapid increase in interest in using coastal habitat restoration as a climate change mitigation tool. This review shows that restoration efforts are able to substantially increase blue carbon stocks, while also having a positive impact on various gaseous fluxes. However, blue carbon increases are spatially variable, due to biophysical factors such as climate and geomorphic setting. While there are potentially hundreds of thousands of hectares of land that may be biophysically suitable for restoration, these activities are still often conducted at small scales and with mixed success. Maximizing potential carbon gains through blue carbon restoration will require managers and coastal planners to overcome the myriad socioeconomic and governance constraints related to land tenure, legislation, target setting and cost, which often push restoration projects into locations that are biophysically unsuitable for plant colonization.
Interventions aimed at reducing prejudice toward refugees have shown promise in industrialized countries. However, the vast majority of refugees are in developing countries. Moreover, while these interventions focus on individual attitude change, attitudes often do not shift in isolation; people are embedded in rich social networks. We conducted a field experiment in northwestern Uganda (host to over a million refugees) and find that perspective-taking warmed individual attitudes there in the short term. We also find that the treatment effect spills over from treated households to control ones along social ties, that spillovers can be positive or negative depending on the source, and that peoples’ attitudes change based on informal conversations with others in the network after the treatment. The findings show the importance of understanding the social process that can reinforce or unravel individual-level attitude change toward refugees; it appears essential to designing interventions with a lasting effect on attitudes.
European chub Leuciscus cephalus collected from five localities in the lowland and subalpine regions of Austria were analysed for oestrogenic effects of endocrine-disrupting chemicals and the presence of the plerocercoid of the tapeworm Ligula intestinalis. Of 1494 chub analysed, only seven (six males, one female) were found to be infected with single, but large plerocercoids up to 15 cm in length. Ligula-infected fish showed comparatively immature gonads, as demonstrated by the gonadosomatic index and gamete developmental stages. Plasma levels of the egg precursor protein vitellogenin also showed concentrations ranging below the detection limit. The present results indicate that chub infected with L. intestinalis and exposed to exogenous oestrogenic compounds can result in reduced gonadal maturation and produce false oestrogen-positive diagnoses in male fish. For plasma vitellogenin levels, L. intestinalis infections can result in false oestrogen-negative diagnoses in male and female fish.
The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery (WCPCCS) will be held in Washington DC, USA, from Saturday, 26 August, 2023 to Friday, 1 September, 2023, inclusive. The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery will be the largest and most comprehensive scientific meeting dedicated to paediatric and congenital cardiac care ever held. At the time of the writing of this manuscript, The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery has 5,037 registered attendees (and rising) from 117 countries, a truly diverse and international faculty of over 925 individuals from 89 countries, over 2,000 individual abstracts and poster presenters from 101 countries, and a Best Abstract Competition featuring 153 oral abstracts from 34 countries. For information about the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery, please visit the following website: [www.WCPCCS2023.org]. The purpose of this manuscript is to review the activities related to global health and advocacy that will occur at the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery.
Acknowledging the need for urgent change, we wanted to take the opportunity to bring a common voice to the global community and issue the Washington DC WCPCCS Call to Action on Addressing the Global Burden of Pediatric and Congenital Heart Diseases. A copy of this Washington DC WCPCCS Call to Action is provided in the Appendix of this manuscript. This Washington DC WCPCCS Call to Action is an initiative aimed at increasing awareness of the global burden, promoting the development of sustainable care systems, and improving access to high quality and equitable healthcare for children with heart disease as well as adults with congenital heart disease worldwide.
We present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder. Phase 1 of the WALLABY pilot survey targeted three
$60\,\mathrm{deg}^{2}$
regions on the sky in the direction of the Hydra and Norma galaxy clusters and the NGC 4636 galaxy group, covering the redshift range of
$z \lesssim 0.08$
. The source catalogue, images and spectra of nearly 600 extragalactic H i detections and kinematic models for 109 spatially resolved galaxies are available. As the pilot survey targeted regions containing nearby group and cluster environments, the median redshift of the sample of
$z \approx 0.014$
is relatively low compared to the full WALLABY survey. The median galaxy H i mass is
$2.3 \times 10^{9}\,{\rm M}_{{\odot}}$
. The target noise level of
$1.6\,\mathrm{mJy}$
per 30′′ beam and
$18.5\,\mathrm{kHz}$
channel translates into a
$5 \sigma$
H i mass sensitivity for point sources of about
$5.2 \times 10^{8} \, (D_{\rm L} / \mathrm{100\,Mpc})^{2} \, {\rm M}_{{\odot}}$
across 50 spectral channels (
${\approx} 200\,\mathrm{km \, s}^{-1}$
) and a
$5 \sigma$
H i column density sensitivity of about
$8.6 \times 10^{19} \, (1 + z)^{4}\,\mathrm{cm}^{-2}$
across 5 channels (
${\approx} 20\,\mathrm{km \, s}^{-1}$
) for emission filling the 30′′ beam. As expected for a pilot survey, several technical issues and artefacts are still affecting the data quality. Most notably, there are systematic flux errors of up to several 10% caused by uncertainties about the exact size and shape of each of the primary beams as well as the presence of sidelobes due to the finite deconvolution threshold. In addition, artefacts such as residual continuum emission and bandpass ripples have affected some of the data. The pilot survey has been highly successful in uncovering such technical problems, most of which are expected to be addressed and rectified before the start of the full WALLABY survey.
Progress towards understanding the aetiology of major depression is compromised by its clinical heterogeneity. The variety of contexts underlying the development of a major depressive episode may contribute to such heterogeneity.
Aims
To compare risk factor profiles for three subgroups of major depression according to episode context.
Method
Using self-report questionnaires and administrative records from the UK Biobank, we characterised three contextual subgroups of major depression: postpartum depression (3581 cases), depression following diagnosis of a chronic disease (409 cases) and a more typical (named heterogeneous) major depression phenotype excluding the two other contexts (34 699 cases). Controls with the same exposure were also defined. We tested each subgroup for association with the polygenic risk scores (PRS) for major depression and with other risk factors previously associated with major depression (bipolar disorder PRS, neuroticism, reported trauma in childhood and adulthood, socioeconomic status, family history of depression, education).
Results
Major depression PRS was associated with all subgroups, but postpartum depression cases had higher PRS than heterogeneous major depression cases (OR = 1.06, 95% CI 1.02–1.10). Relative to heterogeneous depression, postpartum depression was more weakly associated with adulthood trauma and neuroticism. Depression following diagnosis of a chronic disease had weaker association with neuroticism and reported trauma in adulthood and childhood relative to heterogeneous depression.
Conclusions
The observed differences in risk factor profiles according to the context of a major depressive episode help provide insight into the heterogeneity of depression. Future studies dissecting such heterogeneity could help reveal more refined aetiological insights.
There is evidence that the COVID-19 pandemic has negatively affected mental health, but most studies have been conducted in the general population.
Aims
To identify factors associated with mental health during the COVID-19 pandemic in individuals with pre-existing mental illness.
Method
Participants (N = 2869, 78% women, ages 18–94 years) from a UK cohort (the National Centre for Mental Health) with a history of mental illness completed a cross-sectional online survey in June to August 2020. Mental health assessments were the GAD-7 (anxiety), PHQ-9 (depression) and WHO-5 (well-being) questionnaires, and a self-report question on whether their mental health had changed during the pandemic. Regressions examined associations between mental health outcomes and hypothesised risk factors. Secondary analyses examined associations between specific mental health diagnoses and mental health.
Results
A total of 60% of participants reported that mental health had worsened during the pandemic. Younger age, difficulty accessing mental health services, low income, income affected by COVID-19, worry about COVID-19, reduced sleep and increased alcohol/drug use were associated with increased depression and anxiety symptoms and reduced well-being. Feeling socially supported by friends/family/services was associated with better mental health and well-being. Participants with a history of anxiety, depression, post-traumatic stress disorder or eating disorder were more likely to report that mental health had worsened during the pandemic than individuals without a history of these diagnoses.
Conclusions
We identified factors associated with worse mental health during the COVID-19 pandemic in individuals with pre-existing mental illness, in addition to specific groups potentially at elevated risk of poor mental health during the pandemic.
Sleep disturbances are important symptoms to monitor in people with bipolar disorder (BD) but the precise longitudinal relationships between sleep and mood remain unclear. We aimed to examine associations between stable and dynamic aspects of sleep and mood in people with BD, and assess individual differences in the strength of these associations.
Methods
Participants (N = 649) with BD-I (N = 400) and BD-II (N = 249) provided weekly self-reports of insomnia, depression and (hypo)mania symptoms using the True Colours online monitoring tool for 21 months. Dynamic structural equation models were used to examine the interplay between weekly reports of insomnia and mood. The effects of clinical and demographic characteristics on associations were also assessed.
Results
Increased variability in insomnia symptoms was associated with increased mood variability. In the sample as a whole, we found strong evidence of bidirectional relationships between insomnia and depressive symptoms but only weak support for bidirectional relationships between insomnia and (hypo)manic symptoms. We found substantial variability between participants in the strength of prospective associations between insomnia and mood, which depended on age, gender, bipolar subtype, and a history of rapid cycling.
Conclusions
Our results highlight the importance of monitoring sleep in people with BD. However, researchers and clinicians investigating the association between sleep and mood should consider subgroup differences in this relationship. Advances in digital technology mean that intensive longitudinal data on sleep and mood are becoming increasingly available. Novel methods to analyse these data present an exciting opportunity for furthering our understanding of BD.
Relapse and recurrence of depression are common, contributing to the overall burden of depression globally. Accurate prediction of relapse or recurrence while patients are well would allow the identification of high-risk individuals and may effectively guide the allocation of interventions to prevent relapse and recurrence.
Aims
To review prognostic models developed to predict the risk of relapse, recurrence, sustained remission, or recovery in adults with remitted major depressive disorder.
Method
We searched the Cochrane Library (current issue); Ovid MEDLINE (1946 onwards); Ovid Embase (1980 onwards); Ovid PsycINFO (1806 onwards); and Web of Science (1900 onwards) up to May 2021. We included development and external validation studies of multivariable prognostic models. We assessed risk of bias of included studies using the Prediction model risk of bias assessment tool (PROBAST).
Results
We identified 12 eligible prognostic model studies (11 unique prognostic models): 8 model development-only studies, 3 model development and external validation studies and 1 external validation-only study. Multiple estimates of performance measures were not available and meta-analysis was therefore not necessary. Eleven out of the 12 included studies were assessed as being at high overall risk of bias and none examined clinical utility.
Conclusions
Due to high risk of bias of the included studies, poor predictive performance and limited external validation of the models identified, presently available clinical prediction models for relapse and recurrence of depression are not yet sufficiently developed for deploying in clinical settings. There is a need for improved prognosis research in this clinical area and future studies should conform to best practice methodological and reporting guidelines.
Mood disorders are characterised by pronounced symptom heterogeneity, which presents a substantial challenge both to clinical practice and research. Identification of subgroups of individuals with homogeneous symptom profiles that cut across current diagnostic categories could provide insights in to the transdiagnostic relevance of individual symptoms, which current categorical diagnostic systems cannot impart.
Aims
To identify groups of people with homogeneous clinical characteristics, using symptoms of manic and/or irritable mood, and explore differences between groups in diagnoses, functional outcomes and genetic liability.
Method
We used latent class analysis on eight binary self-reported symptoms of manic and irritable mood in the UK Biobank and PROTECT studies, to investigate how individuals formed latent subgroups. We tested associations between the latent classes and diagnoses of psychiatric disorders, sociodemographic characteristics and polygenic risk scores.
Results
Five latent classes were derived in UK Biobank (N = 42 183) and were replicated in the independent PROTECT cohort (N = 4445), including ‘minimally affected’, ‘inactive restless’, active restless’, ‘focused creative’ and ‘extensively affected’ individuals. These classes differed in disorder risk, polygenic risk score and functional outcomes. One class that experienced disruptive episodes of mostly irritable mood largely comprised cases of depression/anxiety, and a class of individuals with increased confidence/creativity reported comparatively lower disruptiveness and functional impairment.
Conclusions
Findings suggest that data-driven investigations of psychopathological symptoms that include sub-diagnostic threshold conditions can complement research of clinical diagnoses. Improved classification systems of psychopathology could investigate a weighted approach to symptoms, toward a more dimensional classification of mood disorders.
From public health to political campaigns, numerous attempts to encourage behavior begin with the spread of information. Of course, seeding new information does not guarantee action, especially when it is difficult for receivers to verify this information. We use a novel design that introduced valuable, actionable information in rural Uganda and reveals the intermediate process that led many in the village to hear the information but only some to act on it. We find that the seeded information spread easily through word of mouth via a simple contagion process. However, acting on the information spread less easily; this process relied instead on endogenously created social information that served to vet, verify, and pass judgment. Our results highlight an important wedge between information that a policy intervention can best control and the behavior that ultimately results.
In arguing for knowledge representation before belief, Phillips et al. presuppose a representational theory of knowledge, a view that has been extensively criticized. As an alternative, we propose an action-based approach to knowledge, conceptualized in terms of skill. We outline the implications of this approach for children's developing social understanding, beginning with sensorimotor interaction and extending to the verbal level.
We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers
$270 \,\mathrm{deg}^2$
of an area covered by the Dark Energy Survey, reaching a depth of 25–30
$\mu\mathrm{Jy\ beam}^{-1}$
rms at a spatial resolution of
$\sim$
11–18 arcsec, resulting in a catalogue of
$\sim$
220 000 sources, of which
$\sim$
180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.
Substantial progress has been made in the standardization of nomenclature for paediatric and congenital cardiac care. In 1936, Maude Abbott published her Atlas of Congenital Cardiac Disease, which was the first formal attempt to classify congenital heart disease. The International Paediatric and Congenital Cardiac Code (IPCCC) is now utilized worldwide and has most recently become the paediatric and congenital cardiac component of the Eleventh Revision of the International Classification of Diseases (ICD-11). The most recent publication of the IPCCC was in 2017. This manuscript provides an updated 2021 version of the IPCCC.
The International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD), in collaboration with the World Health Organization (WHO), developed the paediatric and congenital cardiac nomenclature that is now within the eleventh version of the International Classification of Diseases (ICD-11). This unification of IPCCC and ICD-11 is the IPCCC ICD-11 Nomenclature and is the first time that the clinical nomenclature for paediatric and congenital cardiac care and the administrative nomenclature for paediatric and congenital cardiac care are harmonized. The resultant congenital cardiac component of ICD-11 was increased from 29 congenital cardiac codes in ICD-9 and 73 congenital cardiac codes in ICD-10 to 318 codes submitted by ISNPCHD through 2018 for incorporation into ICD-11. After these 318 terms were incorporated into ICD-11 in 2018, the WHO ICD-11 team added an additional 49 terms, some of which are acceptable legacy terms from ICD-10, while others provide greater granularity than the ISNPCHD thought was originally acceptable. Thus, the total number of paediatric and congenital cardiac terms in ICD-11 is 367. In this manuscript, we describe and review the terminology, hierarchy, and definitions of the IPCCC ICD-11 Nomenclature. This article, therefore, presents a global system of nomenclature for paediatric and congenital cardiac care that unifies clinical and administrative nomenclature.
The members of ISNPCHD realize that the nomenclature published in this manuscript will continue to evolve. The version of the IPCCC that was published in 2017 has evolved and changed, and it is now replaced by this 2021 version. In the future, ISNPCHD will again publish updated versions of IPCCC, as IPCCC continues to evolve.
This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data.
Methods
Individual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1–3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Individual items were then included in ENR and OLS (models 7 and 8). All models were compared to one another and to a null model (mean post-baseline Beck Depression Inventory Second Edition (BDI-II) score in the training data: model 9). Primary outcome: BDI-II scores at 3–4 months.
Results
Models 1–7 all outperformed the null model and model 8. Model performance was very similar across models 1–6, meaning that differential weights applied to the baseline sum scores had little impact.
Conclusions
Any of the modelling techniques (models 1–7) could be used to inform prognostic predictions for depressed adults with differences in the proportions of patients reaching remission based on the predicted severity of depressive symptoms post-treatment. However, the majority of variance in prognosis remained unexplained. It may be necessary to include a broader range of biopsychosocial variables to better adjudicate between competing models, and to derive models with greater clinical utility for treatment-seeking adults with depression.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.