Localized outbreaks of coral disease on Arabian reefs are linked to extreme temperatures and environmental stressors

The Arabian Peninsula borders the hottest reefs in the world, and corals living in these extreme environments can provide insight into the effects of warming on coral health and disease. Here, we examined coral reef health at 17 sites across three regions along the northeastern Arabian Peninsula (Persian Gulf, Strait of Hormuz and Oman Sea) representing a gradient of environmental conditions. The Persian Gulf has extreme seasonal fluctuations in temperature and chronic hypersalinity, whereas the other two regions experience more moderate conditions. Field surveys identified 13 coral diseases including tissue loss diseases of unknown etiology (white syndromes) in Porites, Platygyra, Dipsastraea, Cyphastrea, Acropora and Goniopora; growth anomalies in Porites, Platygyra and Dipsastraea; black band disease in Platygyra, Dipsastraea, Acropora, Echinopora and Pavona; bleached patches in Porites and Goniopora and a disease unique to this region, yellow-banded tissue loss in Porites. The most widespread diseases were Platygyra growth anomalies (52.9% of all surveys), Acropora white syndrome (47.1%) and Porites bleached patches (35.3%). We found a number of diseases not yet reported in this region and found differential disease susceptibility among coral taxa. Disease prevalence was higher on reefs within the Persian Gulf (avg. 2.05%) as compared to reefs within the Strait of Hormuz (0.46%) or Oman Sea (0.25%). A high number of localized disease outbreaks (8 of 17 sites) were found, especially within the Persian Gulf (5 of 8 sites). Across all regions, the majority of variation in disease prevalence (82.2%) was associated with the extreme temperature range experienced by these corals combined with measures of organic pollution and proximity to shore. Thermal stress is known to drive a number of coral diseases, and thus, this region provides a platform to study disease at the edge of corals’ thermal range

Is telephone health coaching a useful population health strategy for supporting older people with multimorbidity? : An evaluation of reach, effectiveness and cost-effectiveness using a 'trial within a cohort'

BACKGROUND: Innovative ways of delivering care are needed to improve outcomes for older people with multimorbidity. Health coaching involves 'a regular series of phone calls between patient and health professional to provide support and encouragement to promote healthy behaviours'. This intervention is promising, but evidence is insufficient to support a wider role in multimorbidity care. We evaluated health coaching in older people with multimorbidity. METHODS: We used the innovative 'Trials within Cohorts' design. A cohort was recruited, and a trial was conducted using a 'patient-centred' consent model. A randomly selected group within the cohort were offered the intervention and were analysed as the intervention group whether they accepted the offer or not. The intervention sought to improve the skills of patients with multimorbidity to deal with a range of long-term conditions, through health coaching, social prescribing and low-intensity support for low mood. RESULTS: We recruited 4377 older people, and 1306 met the eligibility criteria (two or more long-term conditions and moderate 'patient activation'). We selected 504 for health coaching, and 41% consented. More than 80% of consenters received the defined 'dose' of 4+ sessions. In an intention-to-treat analysis, those selected for health coaching did not improve on any outcome (patient activation, quality of life, depression or self-care) compared to usual care. We examined health care utilisation using hospital administrative and self-report data. Patients selected for health coaching demonstrated lower levels of emergency care use, but an increase in the use of planned services and higher overall costs, as well as a quality-adjusted life year (QALY) gain. The incremental cost per QALY was £8049, with a 70-79% probability of being cost-effective at conventional levels of willingness to pay. CONCLUSIONS: Health coaching did not lead to significant benefits on the primary measures of patient-reported outcome. This is likely related to relatively low levels of uptake amongst those selected for the intervention. Demonstrating effectiveness in this design is challenging, as it estimates the effect of being selected for treatment, regardless of whether treatment is adopted. We argue that the treatment effect estimated is appropriate for health coaching, a proactive model relevant to many patients in the community, not just those seeking care. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number ( ISRCTN12286422 )

A nationwide evaluation of bevacizumab-based treatments in pediatric low-grade glioma in the UK: safety, efficacy, visual morbidity, and outcomes

BACKGROUND: Bevacizumab is increasingly used in children with pediatric low-grade glioma (PLGG) despite limited evidence. A nationwide UK service evaluation was conducted to provide larger cohort "real life" safety and efficacy data including functional visual outcomes. METHODS: Children receiving bevacizumab-based treatments (BBT) for PLGG (2009-2020) from 11 centers were included. Standardized neuro-radiological (RANO-LGG) and visual (logMAR visual acuity) criteria were used to assess clinical-radiological correlation, survival outcomes and multivariate prognostic analysis. RESULTS: Eighty-eight children with PLGG received BBT either as 3rd line with irinotecan (85%) or alongside 1st/2nd line chemotherapies (15%). Toxicity was limited and minimal. Partial response (PR, 40%), stable disease (SD, 49%), and progressive disease (PD, 11%) were seen during BBT. However, 65% progressed at 8 months (median) from BBT cessation, leading to a radiology-based 3 yr-progression-free survival (PFS) of 29%. Diencephalic syndrome (P = .03) was associated with adverse PFS. Pre-existing visual morbidity included unilateral (25%) or bilateral (11%) blindness. Improvement (29%) or stabilization (49%) of visual acuity was achieved, more often in patients' best eyes. Vision deteriorated during BBT in 14 (22%), with 3-year visual-PFS of 53%; more often in patients' worst eyes. A superior visual outcome (P = .023) was seen in neurofibromatosis type 1-associated optic pathway glioma (OPG). Concordance between visual and radiological responses was 36%; optimized to 48% using only best eye responses. CONCLUSIONS: BBTs provide effective short-term PLGG control and delay further progression, with a better sustained visual (best > worst eye) than radiological response. Further research could optimize the role of BBT toward a potentially sight-saving strategy in OPG

Fair Play For Girls

This report highlights the urgent need for equitable opportunities for girls in football. The report endorsed by leading figures in the football community and backed by the UK Government, underscores the importance of addressing gender disparities in sports provision and support

A review of energy systems models in the UK: Prevalent usage and categorisation

In this paper, a systematic review of academic literature and policy papers since 2008 is undertaken with an aim of identifying the prevalent energy systems models and tools in the UK. A list of all referenced models is presented and the literature is analysed with regards sectoral coverage and technological inclusion, as well as mathematical structure of models. The paper compares available models using an appropriate classification schema, the introduction of which is aimed at making the model landscape more accessible and perspicuous, thereby enhancing the diversity of models within use. The distinct classification presented in this paper comprises three sections, which specify the model purpose and structure, technological detail and mathematical approach. The schema is not designed to be comprehensive, but rather to be a broad classification with pertinent level of information required to differentiate between models. As an example, the UK model landscape is considered and 22 models are classified in three tables, as per the proposed schema

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals

AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD

Improving care for older people with long-term conditions and social care needs in Salford : the CLASSIC mixed-methods study, including RCT

BackgroundThe Salford Integrated Care Programme (SICP) was a large-scale transformation project to improve care for older people with long-term conditions and social care needs. We report an evaluation of the ability of the SICP to deliver an enhanced experience of care, improved quality of life, reduced costs of care and improved cost-effectiveness.ObjectivesTo explore the process of implementation of the SICP and the impact on patient outcomes and costs.DesignQualitative methods (interviews and observations) to explore implementation, a cohort multiple randomised controlled trial to assess patient outcomes through quasi-experiments and a formal trial, and an analysis of routine data sets and appropriate comparators using non-randomised methodologies.SettingSalford in the north-west of England.ParticipantsOlder people aged ≥ 65 years, carers, and health and social care professionals.InterventionsA large-scale integrated care project with three core mechanisms of integration (community assets, multidisciplinary groups and an ‘integrated contact centre’).Main outcome measuresPatient self-management, care experience and quality of life, and health-care utilisation and costs.Data sourcesProfessional and patient interviews, patient self-report measures, and routine quantitative data on service utilisation.ResultsThe SICP and subsequent developments have been sustained by strong partnerships between organisations. The SICP achieved ‘functional integration’ through the pooling of health and social care budgets, the development of the Alliance Agreement between four organisations and the development of the shared care record. ‘Service-level’ integration was slow and engagement with general practice was a challenge. We saw only minor changes in patient experience measures over the period of the evaluation (both improvements and reductions), with some increase in the use of community assets and care plans. Compared with other sites, the difference in the rates of admissions showed an increase in emergency admissions. Patient experience of health coaching was largely positive, although the effects of health coaching on activation and depression were not statistically significant. Economic analyses suggested that coaching was likely to be cost-effective, generating improvements in quality of life [mean incremental quality-adjusted life-year gain of 0.019, 95% confidence interval (CI) –0.006 to 0.043] at increased cost (mean incremental total cost increase of £150.58, 95% CI –£470.611 to £711.776).LimitationsThe Comprehensive Longitudinal Assessment of Salford Integrated Care study represents a single site evaluation, with consequent limits on external validity. Patient response rates to the cohort survey were ConclusionsThe SICP has been implemented in a way that is consistent with the original vision. However, there has been more rapid success in establishing new integrated structures (such as a formal integrated care organisation), rather than in delivering mechanisms of integration at sufficient scale to have a large impact on patient outcomes.Future workFurther research could focus on each of the mechanisms of integration. The multidisciplinary groups may require improved targeting of patients or disease subgroups to demonstrate effectiveness. Development of a proven model of health coaching that can be implemented at scale is required, especially one that would provide cost savings for commissioners or providers. Similarly, further exploration is required to assess the longer-term benefits of community assets and whether or not health impacts translate to reductions in care use.Trial registrationCurrent Controlled Trials ISRCTN12286422.FundingThis project was funded by the NIHR Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 6, No. 31. See the NIHR Journals Library website for further project information

Mega-analysis of association between obesity and cortical morphology in bipolar disorders:ENIGMA study in 2832 participants

Background: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. Methods: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. Results: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. Conclusions: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.</p

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p