A statistical description of concurrent mixing and crystallization during MORB differentiation: Implications for trace element enrichment

The pattern of trace element enrichment and variability found in differentiated suites of basalts is a simple observable, which nonetheless records a wealth of information on processes occurring from the mantle to crustal magma chambers. The incompatible element contents of some mid-ocean ridge basalt (MORB) sample suites show progressive enrichment beyond the predictions of simple models of fractional crystallization of a single primary melt. Explanations for this over-enrichment have focused on the differentiation processes in crustal magma chambers. Here we consider an additional mechanism and focus instead on the deviation from simple fractionation trends that is possible by mixing of diverse mantle-derived melts supplied to magma chambers. A primary observation motivating this strategy is that there is significant chemical diversity in primitive high-MgO basalts, which single liquid parent models cannot match. Models were developed to simulate the compositional effects of concurrent mixing and crystallization (CMC): diverse parental melts were allowed to mix, with a likelihood that is proportional to the extent of fractional crystallization. Using a simple statistical model to explore the effects of concurrent mixing and crystallization on apparent liquid lines of descent, we show how significant departure from Rayleigh fractionation is possible as a function of the diversity of trace elements in the incoming melts, their primary MgO content, and the relative proportion of enriched to depleted melts. The model was used to make predictions of gradients of trace element enrichment in log[trace element]–MgO space. These predictions were compared with observations from a compilation of global MORB and provide a test of the applicability of CMC to natural systems. We find that by considering the trace element variability of primitive MORB, their MgO contents and degree of enrichment, CMC accurately predicts the pattern of trace element over-enrichment seen in global MORB. Importantly, this model shows that the relationship between over-enrichment and incompatibility can result from mantle processes: the fact that during mantle melting maximum variability is generated in those elements with the smallest bulk $K_\text{d}$. Magma chamber processes are therefore filtering the signal of mantle-derived chemical diversity to produce trace element over-enrichment during differentiation. Finally, we interrogate the global MORB dataset for evidence that trace element over-enrichment varies as a function of melt supply. There is no correlation between over-enrichment and melt supply in the global dataset. Trace element over-enrichment occurs at slow-spreading ridges where extensive steady-state axial magma chambers, the most likely environment for repeated episodes of replenishment, tapping and crystallization, are very rarely detected. This supports a model whereby trace element over-enrichment is an inevitable consequence of chemically heterogeneous melts delivered from the mantle, a process that may operate across all rates of melt supply.The authors would like to thank the Isaac Newton Institute for Mathematical Sciences for its hospitality during the programme ‘Melt in the Mantle’, which was supported by EPSRC Grant Number EP/K032208/1. O.S. was supported by Trinity College Cambridge through a Title A Fellowship and at Caltech by a Geology Option Postdoctoral Fellowship. J.F.R. thanks the Leverhulme Trust for support

Prevalence of type 2 diabetes in psychiatric disorders: an umbrella review with meta-analysis of 245 observational studies from 32 systematic reviews

Aims/hypothesis: Estimates of the global prevalence of type 2 diabetes vary between 6% and 9%. The prevalence of type 2 diabetes has been investigated in psychiatric populations but a critical appraisal of the existing evidence is lacking, and an overview is needed. This umbrella review summarises existing systematic reviews of observational studies investigating the prevalence of type 2 diabetes in people with a psychiatric disorder. / Methods: We searched PubMed, EMBASE, PsycINFO and the Cochrane Database of Systematic Reviews from inception to 17 January 2021 and screened reference lists of included systematic reviews. On the basis of prespecified criteria, we included systematic reviews investigating the prevalence of type 2 diabetes in adults (aged ≥18 years) with a psychiatric disorder. Titles and abstracts of 5155 identified records and full texts of 431 selected studies were screened by two independent reviewers, based on predefined eligibility criteria and an a priori developed extraction form, following the PRISMA and MOOSE guidelines. Risk of bias was assessed with the ROBIS instrument. Data extracted from primary studies were synthesised using random-effects meta-analyses. / Results: A total of 32 systematic reviews with 245 unique primary studies were identified and met inclusion criteria. Twelve had low risk of bias. They reported type 2 diabetes prevalence estimates ranging from 5% to 22% depending on the specific psychiatric disorder. We meta-analysed data for ten categories of psychiatric disorders and found the following prevalence estimates of type 2 diabetes: in people with a sleep disorder: 40%; binge eating disorder: 21%; substance use disorder: 16%; anxiety disorder: 14%; bipolar disorder: 11%; psychosis: 11%; schizophrenia: 10%; a mixed group of psychiatric disorders: 10%; depression: 9%; and in people with an intellectual disability 8%. All meta-analyses revealed high levels of heterogeneity. / Conclusions/interpretation: Type 2 diabetes is a common comorbidity in people with a psychiatric disorder. Future research should investigate whether routine screening for type 2 diabetes and subsequent prevention initiatives for these people are warranted

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

Background: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures. Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies. Results: Methods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated. Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

Comparing orbiter and rover image-based mapping of an ancient sedimentary environment, Aeolis Palus, Gale crater, Mars

This study provides the first systematic comparison of orbital facies maps with detailed ground-based geology observations from the Mars Science Laboratory (MSL) Curiosity rover to examine the validity of geologic interpretations derived from orbital image data. Orbital facies maps were constructed for the Darwin, Cooperstown, and Kimberley waypoints visited by the Curiosity rover using High Resolution Imaging Science Experiment (HiRISE) images. These maps, which represent the most detailed orbital analysis of these areas to date, were compared with rover image-based geologic maps and stratigraphic columns derived from Curiosity's Mast Camera (Mastcam) and Mars Hand Lens Imager (MAHLI). Results show that bedrock outcrops can generally be distinguished from unconsolidated surficial deposits in high-resolution orbital images and that orbital facies mapping can be used to recognize geologic contacts between well-exposed bedrock units. However, process-based interpretations derived from orbital image mapping are difficult to infer without known regional context or observable paleogeomorphic indicators, and layer-cake models of stratigraphy derived from orbital maps oversimplify depositional relationships as revealed from a rover perspective. This study also shows that fine-scale orbital image-based mapping of current and future Mars landing sites is essential for optimizing the efficiency and science return of rover surface operations

Peer-reported bullying, rejection and hallucinatory experiences in childhood

Objective: Psychotic experiences, such as hallucinations, occur commonly in children and have been related to bullying victimization. However, whether bullying perpetration, peer rejection, or peer acceptance are related to hallucinatory experiences has remained under-examined. We used a novel peer nomination method to examine whether (i) bullying perpetration and (ii) social positions within peer networks were associated with future hallucinatory experiences. Methods: This prospective study was embedded in the population-based Generation R Study. Bullying perpetration, peer rejection, and peer acceptance were assessed using peer nominations at age 7 years (N = 925). Using a social network analysis, we estimated social positions within peer rejection and acceptance networks. Bullying victimization was assessed using self-reports. Self-reported hallucinatory experiences were assessed at age 10 years. Analyses were adjusted for sociodemographic covariates. Results: Higher levels of bullying perpetration were prospectively associated with an increased burden of hallucinatory experiences (OR = 1.22, 95% CI 1.05–1.43, p = 0.011). Bullies had a 50% higher, and bully-victims had a 89% higher odds, of endorsing hallucinatory experiences three years later than children who were not involved in bullying (ORbully = 1.50, 95% CI 1.01–2.24, p = 0.045; ORbully-victim = 1.89, 95% CI 1.15–3.10, p = 0.012). Unfavorable positions within peer rejection networks, but not peer acceptance networks, were associated with an increased risk for hallucinatory experiences (ORpeer rejection = 1.24, 95% CI 1.07–1.44, pFDR-corrected = 0.024). Conclusion: Using peer reports, we observed that bullies and socially rejected children have a higher likelihood to report hallucinatory experiences in pre-adolescence. Children who are both a bully and a victim of bullying (ie, bully-victims) may be particularly vulnerable for psychotic experiences

Young off-axis volcanism along the ultraslow-spreading Southwest Indian Ridge

Author Posting. © The Authors, 2010. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature Geoscience 3 (2010): 286-292, doi:10.1038/ngeo824.Mid-ocean ridge crustal accretion occurs continuously at all spreading rates through a combination of magmatic and tectonic processes. Fast to slow spreading ridges are largely built by adding magma to narrowly focused neovolcanic zones. In contrast, ultraslow spreading ridge construction significantly relies on tectonic accretion, which is characterized by thin volcanic crust, emplacement of mantle peridotite directly to the seafloor, and unique seafloor fabrics with variable segmentation patterns. While advances in remote imaging have enhanced our observational understanding of crustal accretion at all spreading rates, temporal information is required in order to quantitatively understand mid-ocean ridge construction. However, temporal information does not exist for ultraslow spreading environments. Here, we utilize U-series eruption ages to investigate crustal accretion at an ultraslow spreading ridge for the first time. Unexpectedly young eruption ages throughout the Southwest Indian ridge rift valley indicate that neovolcanic activity is not confined to the spreading axis, and that magmatic crustal accretion occurs over a wider zone than at faster spreading ridges. These observations not only suggest that crustal accretion at ultraslow spreading ridges is distinct from faster spreading ridges, but also that the magma transport mechanisms may differ as a function of spreading rate.This work was supported by the following NSF grants: NSF-OCE 0137325; NSF-OCE 060383800; and NSF-OCE 062705300

Developing and implementing an integrated delirium prevention system of care:a theory driven, participatory research study

Background: Delirium is a common complication for older people in hospital. Evidence suggests that delirium incidence in hospital may be reduced by about a third through a multi-component intervention targeted at known modifiable risk factors. We describe the research design and conceptual framework underpinning it that informed the development of a novel delirium prevention system of care for acute hospital wards. Particular focus of the study was on developing an implementation process aimed at embedding practice change within routine care delivery. Methods: We adopted a participatory action research approach involving staff, volunteers, and patient and carer representatives in three northern NHS Trusts in England. We employed Normalization Process Theory to explore knowledge and ward practices on delirium and delirium prevention. We established a Development Team in each Trust comprising senior and frontline staff from selected wards, and others with a potential role or interest in delirium prevention. Data collection included facilitated workshops, relevant documents/records, qualitative one-to-one interviews and focus groups with multiple stakeholders and observation of ward practices. We used grounded theory strategies in analysing and synthesising data. Results: Awareness of delirium was variable among staff with no attention on delirium prevention at any level; delirium prevention was typically neither understood nor perceived as meaningful. The busy, chaotic and challenging ward life rhythm focused primarily on diagnostics, clinical observations and treatment. Ward practices pertinent to delirium prevention were undertaken inconsistently. Staff welcomed the possibility of volunteers being engaged in delirium prevention work, but existing systems for volunteer support were viewed as a barrier. Our evolving conception of an integrated model of delirium prevention presented major implementation challenges flowing from minimal understanding of delirium prevention and securing engagement of volunteers alongside practice change. The resulting Prevention of Delirium (POD) Programme combines a multi-component delirium prevention and implementation process, incorporating systems and mechanisms to introduce and embed delirium prevention into routine ward practices. Conclusions: Although our substantive interest was in delirium prevention, the conceptual and methodological strategies pursued have implications for implementing and sustaining practice and service improvements more broadly