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Abstract BackgroundThis research explores the capabilities of ChatGPT-4 in passing the American Board of Family Medicine (ABFM) Certification Examination. Addressing a gap in existing literature, where earlier artificial intelligence (AI) models showed limitations in medical board examinations, this study evaluates the enhanced features and potential of ChatGPT-4, especially in document analysis and information synthesis. ObjectiveThe primary goal is to assess whether ChatGPT-4, when provided with extensive preparation resources and when using sophisticated data analysis, can achieve a score equal to or above the passing threshold for the Family Medicine Board Examinations. MethodsIn this study, ChatGPT-4 was embedded in a specialized subenvironment, “AI Family Medicine Board Exam Taker,” designed to closely mimic the conditions of the ABFM Certification Examination. This subenvironment enabled the AI to access and analyze a range of relevant study materials, including a primary medical textbook and supplementary web-based resources. The AI was presented with a series of ABFM-type examination questions, reflecting the breadth and complexity typical of the examination. Emphasis was placed on assessing the AI’s ability to interpret and respond to these questions accurately, leveraging its advanced data processing and analysis capabilities within this controlled subenvironment. ResultsIn our study, ChatGPT-4’s performance was quantitatively assessed on 300 practice ABFM examination questions. The AI achieved a correct response rate of 88.67% (95% CI 85.08%-92.25%) for the Custom Robot version and 87.33% (95% CI 83.57%-91.10%) for the Regular version. Statistical analysis, including the McNemar test (PP ConclusionsThe study demonstrates that ChatGPT-4, particularly when equipped with specialized preparation and when operating in a tailored subenvironment, shows promising potential in handling the intricacies of medical board examinations. While its performance is comparable with the expected standards for passing the ABFM Certification Examination, further enhancements in AI technology and tailored training methods could push these capabilities to new heights. This exploration opens avenues for integrating AI tools such as ChatGPT-4 in medical education and assessment, emphasizing the importance of continuous advancement and specialized training in medical applications of AI.

Cohesion measure launched from the Family Adaptability and Cohesion Evaluation Scale (FACES) is a well-known instrument to assess family functioning. It is essential to perform a measurement equivalence test of cohesion targeting racially diverse families. The web-based self-administered survey was performed and 291 college/university students’ responses in Ohio were collected (Whites = 37.5%, Hispanics = 23%, Asians = 23%, and Blacks = 16.5%). This study explicated measurement equivalence for family cohesion structure (balanced cohesion, disengagement, enmeshed). The multiple group analysis was performed to investigate whether parameters in the measurement models of the “cohesion sub-structures (balanced cohesion, disengagement, enmeshed; 7 items of each)” were equivalent across the four racial groups. While “balanced cohesion” and “disengagement” structures showed measurement invariance across the groups, the “enmeshed” structure showed significant measurement variance across the groups. Two-items, “Family members feel pressured to spend most free time together” and “We feel too connected to each other” were inadequate for Hispanics’ enmeshment. One-item, “Family members have little need for friends outside the family” was inadequate to explain enmeshment of Blacks and Asians. Professionals should be aware of possible misinterpretations of results from the cohesion measure of FACES IV when they particularly assess the enmeshment status of racially diverse families with closer attention to cross-cultural comparability.

Introduction Smartwatches have become ubiquitous for tracking health metrics. These data sets hold substantial potential for enhancing healthcare and public health initiatives; it may be used to track chronic health conditions, detect previously undiagnosed health conditions and better understand public health trends. By first understanding the factors influencing one’s continuous use of the device, it will be advantageous to assess factors that may influence a person’s willingness to share their individual data sets. This study seeks to comprehensively understand the factors influencing the continued use of these devices and people’s willingness to share the health data they generate.Methods and analysis A two-section online survey of smartwatch users over the age of 18 will be conducted (n ≥200). The first section, based on the expectation-confirmation model, will assess factors influencing continued use of smartwatches while the second section will assess willingness to share the health data generated from these devices. Survey data will be analysed descriptively and based on structural equation modelling.Subsequently, six focus groups will be conducted to further understand the issues raised in the survey. Each focus group (n=6) will consist of three smartwatch users: a general practitioner, a public health specialist and an IT specialist. Young smartwatch users (aged 18–44) will be included in three of the focus groups and middle-aged smartwatch users (aged 45–64) will be included in the other three groups. This is to enhance comparison of opinions based on age groups. Data from the focus groups will be analysed using the microinterlocutor approach and an executive summary.After the focus group, participants will complete a brief survey to indicate any changes in their opinions resulting from the discussion.Ethics and dissemination The results of this study will be disseminated through publication in a peer-reviewed journal, and all associated data will be deposited in a relevant, publicly accessible data repository to ensure transparency and facilitate future research endeavours.This study was approved by the Social Research Ethic Committee (SREC), University College Cork—SREC/SOM/21062023/2.

Background There are significant clinical, policy and societal concerns about the impact on young people (YP), from admission to psychiatric wards far from home. However, research evidence is scarce.Aims To investigate the impact of at-distance admissions to general adolescent units, from the perspectives of YP, parents/carers and healthcare professionals (HCPs) including service commissioners, to inform clinical practice, service development and policy.Method Semistructured interviews with purposive samples of YP aged 13–17 years (n=28) and parents/carers (n=19) across five large regions in England, and a national sample of HCPs (n=51), were analysed using a framework approach.Results There was considerable agreement between YP, parents/carers and HCPs on the challenges of at-distance admissions. YP and parents/carers had limited or no involvement in decision-making processes around admission and highlighted a lack of available information about individual units. Being far from home posed challenges with maintaining home contact and practical/financial challenges for families visiting. HCPs struggled with ensuring continuity of care, particularly around maintaining access to local clinical teams and educational support. However, some YP perceived separation from their local environment as beneficial because it removed them from unhelpful environments. At-distance admissions provided respite for some families struggling to support their child.Conclusions At-distance admissions lead to additional distress, uncertainty, compromised continuity of care and educational, financial and other practical difficulties, some of which could be better mitigated. For a minority, there are some benefits from such admissions.Clinical implications Standardised online information, accessible prior to admission, is needed for all Child and Adolescent Mental Health Services units. Additional practical and financial burden placed on families needs greater recognition and consideration of potential sources of support. Policy changes should incorporate findings that at-distance or adult ward admissions may be preferable in certain circumstances.

Background The increasing prevalence and acuity of mental disorders among children and adolescents have placed pressure on services, including inpatient care, and resulted in young people being admitted at-distance or to adult wards. Little empirical research has investigated such admissions.Objective To determine the incidence, clinical characteristics and 6-month outcomes of patients aged 13–17 years old admitted at-distance (>50 miles from home or out of region) to general adolescent psychiatric wards or to adult psychiatric wards.Methods Surveillance over 13 months (February 2021–February 2022) using the Child and Adolescent Psychiatry Surveillance System including baseline and 6-month follow-up questionnaires.Findings Data were collected about 290 admissions (follow-up rate 99% (288 of 290); sample were 73% female, mean age 15.8 years). The estimated adjusted yearly incidence of at-distance admission was 13.7–16.9 per 100 000 young people 13–17 years old. 38% were admitted >100 miles from home and 8% >200 miles. The most common diagnoses at referral were depression (34%) and autism spectrum disorder (20%); other common referral concerns included suicide risk (80%), emotional dysregulation (53%) and psychotic symptoms (22%). Over two-fifths (41%) waited ≥1 week for a bed, with 55% waiting in general hospital settings. At 6-month follow-up, 20% were still in hospital, the majority in at-distance placements.Conclusions At-distance and adult ward admissions for patients aged

Objective: Standard nerve excitability testing (NET) predominantly assesses Aα- and Aβ-fiber function, but a method examining small afferents would be of great interest in pain studies. Here, we examined the properties of a novel perception threshold tracking (PTT) method that preferentially activates Aδ-fibers using weak currents delivered by a novel multipin electrode and compared its reliability with NET. Methods: Eighteen healthy subjects (mean age:34.06 ± 2.0) were examined three times with motor and sensory NET and PTT in morning and afternoon sessions on the same day (intra-day reliability) and after a week (inter-day reliability). NET was performed on the median nerve, while PTT stimuli were delivered through a multipin electrode located on the forearm. During PTT, subjects indicated stimulus perception via a button press and the intensity of the current was automatically increased or decreased accordingly by Qtrac software. This allowed changes in the perception threshold to be tracked during strength-duration time constant (SDTC) and threshold electrotonus protocols. Results: The coefficient of variation (CoV) and interclass coefficient of variation (ICC) showed good–excellent reliability for most NET parameters. PTT showed poor reliability for both SDTC and threshold electrotonus parameters. There was a significant correlation between large (sensory NET) and small (PTT) fiber SDTC when all sessions were pooled (r = 0.29, p = 0.03). Conclusions: Threshold tracking technique can be applied directly to small fibers via a psychophysical readout, but with the current technique, the reliability is poor. Significance: Further studies are needed to examine whether Aβ-fiber SDTC may be a surrogate biomarker for peripheral nociceptive signalling.

Abstract Aim To describe the spectrum of parasagittal injury on MRI studies performed on children following severe perinatal term hypoxia–ischaemia, using a novel MRI grading system, and propose a new central pattern correlated with neuropathologic features. Methods MR scans of 297 patients with perinatal term hypoxia–ischaemia were evaluated for typical patterns of brain injury. A total of 83 patients that demonstrated the central/basal ganglia–thalamus and perirolandic pattern of injury were categorised according to the degree of severity. The perirolandic injury was graded by the degree of interhemispheric widening, paracentral lobule involvement and perirolandic cortex destruction leading to a tiered categorisation. Of these 83 patients, 19 had the most severe subtype of injury. A detailed analysis of the clinical data of a subset of 11 of these 19 patients was conducted. Results We demonstrated the mild subtype in 21/83(25%), the moderate subtype in 22/83(27%) and the severe subtype in 21/83(25%). A fourth pattern was identified in 19/83(23%) patients with a diamond-shaped expansion of the interhemispheric fissure, concomitant thalamic, putaminal, hippocampal and other smaller substrate involvement indicative of the most destructive subtype. Conclusions We propose a new MR grading system of injury at the parasagittal perirolandic region related to severe, sustained central perinatal term hypoxia–ischaemia. We also introduce a previously undescribed pattern of injury, the most severe form of this spectrum, seen especially after prolongation of the second stage of labour. This constellation of high metabolic substrate, targeted tissue destruction is consistently demonstrated by MRI, termed the massive paramedian injury pattern.

Summary: Protein coding genes were originally identified with sequence-based definitions that included a 100-codon cutoff to avoid annotating irrelevant open reading frames. However, many active proteins contain less than 100 amino acids. Indeed, functional genetics, ribosome profiling, and proteomic profiling have identified many short, translated open reading frames, including those with biologically active peptide products (microproteins). Yet, functions for most of these peptide products remain unknown. Because microproteins often act as key signals or fine-tune processes, animal development has already revealed functions for a handful of microproteins and provides an ideal context to uncover additional microprotein functions. However, many mRNAs during early development are maternally provided and hinder targeted mutagenesis approaches to characterize developmental microprotein functions. The recently established, RNA-targeting CRISPR-Cas13d system in zebrafish overcomes this barrier and produces potent knockdown of targeted mRNA, including maternally provided mRNA, and enables flexible, efficient interrogation of microprotein functions in animal development.

Genetic modification is one possible strategy to generate bananas (Musa spp.) with resistance to the soil-borne pathogen causing Fusarium wilt. The availability of banana root-specific promoters to target transgene expression to the sites of infection would be beneficial. We have assessed 18 promoter sequences derived from a range of plant species for their expression profiles in banana tissues to identify those with root-specific activity. Promoter sequences were isolated and fused to the β-glucuronidase (GUS) gene to assess their expression levels and tissue specificity in both banana and the model plant tobacco. Two heterologous promoters conferring high root expression levels in banana were identified, including a β‐glucosidase 1 (GLU1) promoter from maize and the RB7-type tonoplast intrinsic protein (TIP)-2 promoter from strawberry. Further, a novel Musa TIP2-2 promoter sequence was isolated and characterized which, when fused to the GUS gene, conferred very high GUS expression levels in banana roots. These promoters will expand the options for the control of gene expression in genetically modified bananas, providing a tool to develop plants with resistance not only to soil-borne diseases such as Fusarium wilt, but also for the improvement of other traits, such as nematode resistance, nutrition or abiotic stress resistance.

Abstract Microstructural alterations in cortico-subcortical connections are thought to be present in obsessive–compulsive disorder (OCD). However, prior studies have yielded inconsistent findings, perhaps because small sample sizes provided insufficient power to detect subtle abnormalities. Here we investigated microstructural white matter alterations and their relation to clinical features in the largest dataset of adult and pediatric OCD to date. We analyzed diffusion tensor imaging metrics from 700 adult patients and 645 adult controls, as well as 174 pediatric patients and 144 pediatric controls across 19 sites participating in the ENIGMA OCD Working Group, in a cross-sectional case-control magnetic resonance study. We extracted measures of fractional anisotropy (FA) as main outcome, and mean diffusivity, radial diffusivity, and axial diffusivity as secondary outcomes for 25 white matter regions. We meta-analyzed patient-control group differences (Cohen’s d) across sites, after adjusting for age and sex, and investigated associations with clinical characteristics. Adult OCD patients showed significant FA reduction in the sagittal stratum (d = −0.21, z = −3.21, p = 0.001) and posterior thalamic radiation (d = −0.26, z = −4.57, p

The use of antibodies in the treatment of lung diseases is of increasing interest especially as the search for COVID-19 therapies has unfolded. Historically, the use of antibody therapy was based on multiple targets including receptors involved in local hyper-reactivity in asthma, viruses and micro-organisms involved in a variety of pulmonary infectious disease. Generally, protein therapeutics pose challenges with respect to formulation and delivery to retain activity and assure therapy. The specificity of antibodies amplifies the need for attention to molecular integrity not only in formulation but also during aerosol delivery for pulmonary administration. Drug product development can be viewed from considerations of route of administration, dosage form, quality, and performance measures. Nebulizers and dry powder inhalers have been used to deliver protein therapeutics and each has its advantages that should be matched to the needs of the drug and the disease. This review offers insight into quality and performance barriers and the opportunities that arise from meeting them effectively.

PURPOSEThe global pediatric oncology clinical research landscape, particularly in Central and South America, Africa, and Asia, which bear the highest burden of global childhood cancer cases, is less characterized in the literature. Review of how existing pediatric cancer clinical trial groups internationally have been formed and how their research goals have been pursued is critical for building global collaborative research and data-sharing efforts, in line with the WHO Global Initiative for Childhood Cancer.METHODSA narrative literature review of collaborative groups performing pediatric cancer clinical research in each continent was conducted. An inventory of research groups was assembled and reviewed by current pediatric cancer regional and continental leaders. Each group was narratively described with identification of common structural and research themes among consortia.RESULTSThere is wide variability in the structure, history, and goals of pediatric cancer clinical trial collaborative groups internationally. Several continental regions have longstanding endogenously-formed clinical trial groups that have developed and published numerous adapted treatment regimens to improve outcomes, whereas other regions have consortia focused on developing foundational database registry infrastructure supported by large multinational organizations or twinning relationships.CONCLUSIONThere cannot be a one-size-fits-all approach to increasing collaboration between international pediatric cancer clinical trial groups, as this requires a nuanced understanding of local stakeholders and resources necessary to form partnerships. Needs assessments, performed either by local consortia or in conjunction with international partners, have generated productive clinical trial infrastructure. To achieve the goals of the Global Initiative for Childhood Cancer, global partnerships must be sufficiently granular to account for the distinct needs of each collaborating group and should incorporate grassroots approaches, robust twinning relationships, and implementation science.

Abstract Background Due to limited duration of follow up in clinical trials of cancer treatments, estimates of lifetime survival benefits are typically derived using statistical extrapolation methods. To justify the method used, a range of approaches have been proposed including statistical goodness-of-fit tests and comparing estimates against a previous data cut (i.e. interim data collected). In this study, we extend these approaches by presenting a range of extrapolations fitted to four pre-planned data cuts from the JAVELIN Merkel 200 (JM200) trial. By comparing different estimates of survival and goodness-of-fit as JM200 data mature, we undertook an iterative process of fitting and re-fitting survival models to retrospectively identify early indications of likely long-term survival. Methods Standard and spline-based parametric models were fitted to overall survival data from each JM200 data cut. Goodness-of-fit was determined using an assessment of the estimated hazard function, information theory-based methods and objective comparisons of estimation accuracy. Best-fitting extrapolations were compared to establish which one provided the most accurate estimation, and how statistical goodness-of-fit differed. Results Spline-based models provided the closest fit to the final JM200 data cut, though all extrapolation methods based on the earliest data cut underestimated the ‘true’ long-term survival (difference in restricted mean survival time [RMST] at 36 months: − 1.1 to − 0.5 months). Goodness-of-fit scores illustrated that an increasingly flexible model was favored as data matured. Given an early data cut, a more flexible model better aligned with clinical expectations could be reasonably justified using a range of metrics, including RMST and goodness-of-fit scores (which were typically within a 2-point range of the statistically ‘best-fitting’ model). Conclusions Survival estimates from the spline-based models are more aligned with clinical expectation and provided a better fit to the JM200 data, despite not exhibiting the definitively ‘best’ statistical goodness-of-fit. Longer-term data are required to further validate extrapolations, though this study illustrates the importance of clinical plausibility when selecting the most appropriate model. In addition, hazard-based plots and goodness-of-fit tests from multiple data cuts present useful approaches to identify when a more flexible model may be advantageous. Trial registration JAVELIN Merkel 200 was registered with ClinicalTrials.gov as NCT02155647 on June 4, 2014.

Abstract Effective conservation requires accurate data on population genetic diversity, inbreeding, and genetic structure. Increasingly, scientists are adopting genetic non‐invasive sampling (gNIS) as a cost‐effective population‐wide genetic monitoring approach. gNIS has, however, known limitations which may impact the accuracy of downstream genetic analyses. Here, using high‐quality single nucleotide polymorphism (SNP) data from blood/tissue sampling of a free‐ranging koala population (n = 430), we investigated how the reduced SNP panel size and call rate typical of genetic non‐invasive samples (derived from experimental and field trials) impacts the accuracy of genetic measures, and also the effect of sampling intensity on these measures. We found that gNIS at small sample sizes (14% of population) can provide accurate population diversity measures, but slightly underestimated population inbreeding coefficients. Accurate measures of internal relatedness required at least 33% of the population to be sampled. Accurate geographic and genetic spatial autocorrelation analysis requires between 28% and 51% of the population to be sampled. We show that gNIS at low sample sizes can provide a powerful tool to aid conservation decision‐making and provide recommendations for researchers looking to apply these techniques to free‐ranging systems.

Miniaturized components have significant potential for portable applications. Here, the authors demonstrate a spectrometer and hyperspectral imager based on photonic-crystal slabs which can enable single-shot imaging on a compact chip.

The human brain grows the most dramatically during the perinatal and early post-natal periods, during which pre-term birth or perinatal injury that may alter brain structure and lead to developmental anomalies. Thus, characterizing cortical thickness of developing brains remains an important goal. However, this task is often complicated by inaccurate cortical surface extraction due to small-size brains. Here, we propose a novel complex framework for the reconstruction of neonatal WM and pial surfaces, accounting for large partial volumes due to small-size brains. The proposed approach relies only on T1-weighted images unlike previous T2-weighted image-based approaches while only T1-weighted images are sometimes available under the different clinical/research setting. Deep neural networks are first introduced to the neonatal magnetic resonance imaging (MRI) pipeline to address the mis-segmentation of brain tissues. Furthermore, this pipeline enhances cortical boundary delineation using combined models of the cerebrospinal fluid (CSF)/GM boundary detection with edge gradient information and a new skeletonization of sulcal folding where no CSF voxels are seen due to the limited resolution. We also proposed a systematic evaluation using three independent datasets comprising 736 pre-term and 97 term neonates. Qualitative assessment for reconstructed cortical surfaces shows that 86.9% are rated as accurate across the three site datasets. In addition, our landmark-based evaluation shows that the mean displacement of the cortical surfaces from the true boundaries was less than a voxel size (0.532 ± 0.035 mm). Evaluating the proposed pipeline (namely NEOCIVET 2.0) shows the robustness and reproducibility across different sites and different age-groups. The mean cortical thickness measured positively correlated with post-menstrual age (PMA) at scan (p < 0.0001); Cingulate cortical areas grew the most rapidly whereas the inferior temporal cortex grew the least rapidly. The range of the cortical thickness measured was biologically congruent (1.3 mm at 28 weeks of PMA to 1.8 mm at term equivalent). Cortical thickness measured on T1 MRI using NEOCIVET 2.0 was compared with that on T2 using the established dHCP pipeline. It was difficult to conclude that either T1 or T2 imaging is more ideal to construct cortical surfaces. NEOCIVET 2.0 has been open to the public through CBRAIN (https://mcin-cnim.ca/technology/cbrain/), a web-based platform for processing brain imaging data.

Background: When psychosis emerges in young people there is a risk of poorer outcomes, and access to evidence-based treatments is paramount. The current evidence base is limited. Antipsychotic medications show only a small benefit over placebo, but young people experience more side effects than adults. There is sparse evidence for psychological intervention. Research is needed to determine the clinical effectiveness and cost-effectiveness of psychological intervention versus antipsychotic medication versus a combined treatment for adolescents with psychosis. Objectives: The objective of Managing Adolescent first-episode Psychosis: a feasibility Study (MAPS) was to determine the feasibility of conducting a definitive trial to answer the question of clinical effectiveness and cost-effectiveness of these three treatment options. Design: This was a prospective, randomised, open-blinded, evaluation feasibility trial with a single blind. Participants were allocated 1 : 1 : 1 to receive antipsychotic medication, psychological intervention or a combination of both. A thematic qualitative study explored the acceptability and feasibility of the trial. Setting: Early intervention in psychosis services and child and adolescent mental health services in Manchester, Oxford, Lancashire, Sussex, Birmingham, Norfolk and Suffolk, and Northumberland, Tyne and Wear. Participants: People aged 14–18 years experiencing a first episode of psychosis either with an International Classification of Diseases, Tenth Revision, schizophrenia spectrum diagnosis or meeting the entry criteria for early intervention in psychosis who had not received antipsychotic medication or psychological intervention within the last 3 months. Interventions: Psychological intervention involved up to 26 hours of cognitive–behavioural therapy and six family intervention sessions over 6 months, with up to four booster sessions. Antipsychotic medication was prescribed by the participant’s psychiatrist in line with usual practice. Combined treatment was a combination of psychological intervention and antipsychotic medication. Main outcome measures: The primary outcome was feasibility (recruitment, treatment adherence and retention). We used a three-stage progression criterion to determine feasibility. Secondary outcomes were psychosis symptoms, recovery, anxiety and depression, social and educational/occupational functioning, drug and alcohol use, health economics, adverse/metabolic side effects and adverse/serious adverse events. Results: We recruited 61 out of 90 (67.8%; amber zone) potential participants (psychological intervention, n = 18; antipsychotic medication, n = 22; combined treatment, n = 21). Retention to follow-up was 51 out of 61 participants (83.6%; green zone). In the psychological intervention arm and the combined treatment arm, 32 out of 39 (82.1%) participants received six or more sessions of cognitive–behavioural therapy (green zone). In the combined treatment arm and the antipsychotic medication arm, 28 out of 43 (65.1%) participants received antipsychotic medication for 6 consecutive weeks (amber zone). There were no serious adverse events related to the trial and one related adverse event. Overall, the number of completed secondary outcome measures, including health economics, was small. Limitations: Medication adherence was determined by clinician report, which can be biased. The response to secondary outcomes was low, including health economics. The small sample size obtained means that the study lacked statistical power and there will be considerable uncertainty regarding estimates of treatment effects. Conclusions: It is feasible to conduct a trial comparing psychological intervention with antipsychotic medication and a combination treatment in young people with psychosis with some adaptations to the design, including adaptations to collection of health economic data to determine cost-effectiveness. Future work: An adequately powered definitive trial is required to provide robust evidence. Trial registration: Current Controlled Trials ISRCTN80567433. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 4. See the NIHR Journals Library website for further project information.

The 45th Annual Scientific Meeting of the Nutrition Society of Australia was held virtually from 2–3 December 2021. The theme of the meeting was Nutrition: Opportunities for Nutrition Science in a New Era. Abstracts were submitted from 13 countries. A total of 326 registrants attended the conference, and 134 papers were presented consisting of 6 plenary, 54 oral and 74 poster presentations. This issue presents the proceedings of this meeting in the form of abstracts for papers presented at the conference.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Book Review: Bruce Isaacs, The Orientation of Future Cinema: Technology, Aesthetics, Spectacle. Bloomsbury, 2014. 320 pp. ISBN 9781628924312 (paperback)

The newly recognized Fusarium wilt pathogen tropical race 4 is threatening worldwide banana production. Here, the authors transform Cavendish bananas with a resistance gene, RGA2, from diploid banana or a nematode-derived gene, Ced9, and confer resistance to natural infection under field conditions.

Abstract It can be argued that the controversy over paediatric bipolar disorder has been useful in highlighting the issue of bipolar disorder in youths generally. Arising out of this controversy is the recognition that, besides a more uniformed approach to diagnosis, the issue of the disparity in treatments between the US and UK, especially psychopharmacology, needs addressing.

This study covers the investigation into the reduction of rare-earth magnets in a permanent magnet (PM) machine via the use of multiple rotors to enable a PM generator to be comprised of mixed magnetic elements, hereafter referred to as MME, by substituting ferrite materials into some rotors. The particular machine covered in this paper featured four rotors, with two on the external sides and two inside, along with a trio of stators interlaced between the rotors. The efficiency, power, and cost of this machine are compared herein to explore available benefits of such a configuration as described. It was shown from the finite element analysis results that there was a clear benefit to using cheap ferrite materials in some rotors but not all, allowing for a huge cost decrease while only a small decrease in efficiency. The machine's purpose was for use in a low speed, direct-drive, wind turbine. Therefore, the rated operating speed was required to be very low and was chosen to be 180 RPM which meant 40 poles were needed on the rotors to achieve 10 kVA at 60 Hz.

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses.Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods.Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models.Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.

Background Controversy surrounds the diagnosis and prevalence of paediatric bipolar disorder, with estimates varying considerably between countries. Aims To determine the international hospital discharge rates for paediatric bipolar disorder compared with all other psychiatric diagnoses. Method We used national data-sets from 2000 to 2010 from England, Australia, New Zealand, the USA and Germany. Results For those aged under 20 years, the discharge rates for paediatric bipolar disorder per 100 000 population were: USA 95.6, Australia 11.7, New Zealand 6.3, Germany 1.5 and England 0.9. The most marked divergence in discharge rates was in 5- to 9-year-olds: USA 27, New Zealand 0.22, Australia 0.14, Germany 0.03 and England 0.00. Conclusions The disparity between US and other discharge rates for paediatric bipolar disorder is markedly greater than the variation for child psychiatric discharge rates overall, and for adult rates of bipolar disorder. This suggests there may be differing diagnostic practices for paediatric bipolar disorder in the USA.