Functional topography of the neocortex predicts covariation in complex cognitive and basic motor abilities.

Although higher-order cognitive and lower-order sensorimotor abilities are generally regarded as distinct and studied separately, there is evidence that they not only covary but also that this covariation increases across the lifespan. This pattern has been leveraged in clinical settings where a simple assessment of sensory or motor ability (e.g. hearing, gait speed) can forecast age-related cognitive decline and risk for dementia. However, the brain mechanisms underlying cognitive, sensory, and motor covariation are largely unknown. Here, we examined whether such covariation in midlife reflects variability in common versus distinct neocortical networks using individualized maps of functional topography derived from BOLD fMRI data collected in 769 45-year-old members of a population-representative cohort. Analyses revealed that variability in basic motor but not hearing ability reflected individual differences in the functional topography of neocortical networks typically supporting cognitive ability. These patterns suggest that covariation in motor and cognitive abilities in midlife reflects convergence of function in higher-order neocortical networks and that gait speed may not be simply a measure of physical function but rather an integrative index of nervous system health.

Exploring associations of population characteristics and tobacco and vape retailer density and proximity in Australia: a scoping review.

OBJECTIVE: This scoping review synthesises Australian evidence on associations between tobacco and vape retailer density/proximity and various population measures and smoking behaviour to identify research gaps and inform future policy and strategies. DATA SOURCES: Following Joanna Briggs Institute methodology, relevant studies published in English since 2003 were identified via searches of eight databases in March and August 2023. STUDY SELECTION: Two reviewers independently completed screening procedures. Eligible studies were from Australia and described associations between tobacco or vape retailer density/proximity and adult or youth smoking/vaping prevalence or behaviours, neighbourhood socioeconomic status, geographic location, school locations and/or Indigenous status. DATA EXTRACTION: Results are reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. DATA SYNTHESIS: Of 794 publications screened, 12 studies from 6 Australian states were included. Six studies from five states reported statistically significant associations between neighbourhood-level socioeconomic disadvantage and tobacco retailer density, yet only two studies from two states found a significant relationship between retailer density and adult smoking prevalence. Increasing retailer density was consistently significantly associated with increasing geographical remoteness in three states. No studies explored associations with tobacco retailer proximity or vape retailer density/proximity. CONCLUSIONS: Despite a moderate number of studies overall, state-level evidence is limited, and unknown for Australian territories. Evidence from five Australian states reflects the international evidence that increasing retailer density is significantly associated with increasing socioeconomic disadvantage and remoteness, supporting the need for tobacco supply-based policies. Further research is required to understand the impact of retailer density and adult and youth smoking prevalence in Australia.

Childhood self-control forecasts the pace of midlife aging and preparedness for old age.

The ability to control one's own emotions, thoughts, and behaviors in early life predicts a range of positive outcomes in later life, including longevity. Does it also predict how well people age? We studied the association between self-control and midlife aging in a population-representative cohort of children followed from birth to age 45 y, the Dunedin Study. We measured children's self-control across their first decade of life using a multi-occasion/multi-informant strategy. We measured their pace of aging and aging preparedness in midlife using measures derived from biological and physiological assessments, structural brain-imaging scans, observer ratings, self-reports, informant reports, and administrative records. As adults, children with better self-control aged more slowly in their bodies and showed fewer signs of aging in their brains. By midlife, these children were also better equipped to manage a range of later-life health, financial, and social demands. Associations with children's self-control could be separated from their social class origins and intelligence, indicating that self-control might be an active ingredient in healthy aging. Children also shifted naturally in their level of self-control across adult life, suggesting the possibility that self-control may be a malleable target for intervention. Furthermore, individuals' self-control in adulthood was associated with their aging outcomes after accounting for their self-control in childhood, indicating that midlife might offer another window of opportunity to promote healthy aging.

Childhood blood-lead level predicts lower general, non-selective hippocampal subfield volumes in midlife.

Millions of adults and children are exposed to high levels of lead, a neurotoxicant, each year. Recent evidence suggests that lead exposure may precipitate neurodegeneration, particularly if the exposure occurs early or late in life, with unique alterations to the structure or function of specific subfields of the hippocampus, a region involved in memory and Alzheimer's disease. It has been proposed that specific hippocampal subfields may thus be useful biomarkers for lead-associated neurological disease. We turned to a population-representative New Zealand birth cohort where the extent of lead exposure was not confounded by social class (the Dunedin Study; born 1972-1973 and followed to age 45) to test the hypothesis that early life lead exposure (blood-lead level at age 11 years) is associated with smaller MRI-assessed gray matter volumes of specific subfields of the hippocampus at age 45 years. Among the 508 Dunedin Study members with childhood lead data and adult MRI data passing quality control (93.9 % of those with lead data who attended the age-45 assessment wave, 240[47.2 %] female), childhood blood-lead levels ranged from 4 to 31 µg/dL (M[SD]=10.9[4.6]). Total hippocampal volumes were lower among adults with higher childhood blood-lead levels (b=-102.6 mm3 per 5 ug/dL-unit greater blood-lead level, 95 %CI: -175.4 to -29.7, p=.006, ß=-.11), as were all volumes of the 24 hemisphere-specific subfields of the hippocampus. Of these 24 subfields, 20 demonstrated negative lead-associations greater than ß=-.05 in size, 14 were statistically significant after adjustment for multiple comparisons (pFDR<.05), and 9 remained significant after adjustment for potential confounders and multiple comparisons. Children exposed to lead demonstrate smaller volumes across all subfields of the hippocampus in midlife. The hypothesis that lead selectively impairs specific subfields of the hippocampus, or that specific subfields may be markers for lead-associated neurological disease, requires further evaluation.

Dementia, dementia's risk factors and premorbid brain structure are concentrated in disadvantaged areas: National register and birth-cohort geographic analyses.

INTRODUCTION: Dementia risk may be elevated in socioeconomically disadvantaged neighborhoods. Reasons for this remain unclear, and this elevation has yet to be shown at a national population level. METHODS: We tested whether dementia was more prevalent in disadvantaged neighborhoods across the New Zealand population (N = 1.41 million analytic sample) over a 20-year observation. We then tested whether premorbid dementia risk factors and MRI-measured brain-structure antecedents were more prevalent among midlife residents of disadvantaged neighborhoods in a population-representative NZ-birth-cohort (N = 938 analytic sample). RESULTS: People residing in disadvantaged neighborhoods were at greater risk of dementia (HR per-quintile-disadvantage-increase = 1.09, 95% confidence interval [CI]:1.08-1.10) and, decades before clinical endpoints typically emerge, evidenced elevated dementia-risk scores (CAIDE, LIBRA, Lancet, ANU-ADRI, DunedinARB; ß's 0.31-0.39) and displayed dementia-associated brain structural deficits and cognitive difficulties/decline. DISCUSSION: Disadvantaged neighborhoods have more residents with dementia, and decades before dementia is diagnosed, residents have more dementia-risk factors and brain-structure antecedents. Whether or not neighborhoods causally influence risk, they may offer scalable opportunities for primary dementia prevention.

Test-retest reliability and predictive utility of a macroscale principal functional connectivity gradient.

Mapping individual differences in brain function has been hampered by poor reliability as well as limited interpretability. Leveraging patterns of brain-wide functional connectivity (FC) offers some promise in this endeavor. In particular, a macroscale principal FC gradient that recapitulates a hierarchical organization spanning molecular, cellular, and circuit level features along a sensory-to-association cortical axis has emerged as both a parsimonious and interpretable measure of individual differences in behavior. However, the measurement reliabilities of this FC gradient have not been fully evaluated. Here, we assess the reliabilities of both global and regional principal FC gradient measures using test-retest data from the young adult Human Connectome Project (HCP-YA) and the Dunedin Study. Analyses revealed that the reliabilities of principal FC gradient measures were (1) consistently higher than those for traditional edge-wise FC measures, (2) higher for FC measures derived from general FC (GFC) in comparison with resting-state FC, and (3) higher for longer scan lengths. We additionally examined the relative utility of these principal FC gradient measures in predicting cognition and aging in both datasets as well as the HCP-aging dataset. These analyses revealed that regional FC gradient measures and global gradient range were significantly associated with aging in all three datasets, and moderately associated with cognition in the HCP-YA and Dunedin Study datasets, reflecting contractions and expansions of the cortical hierarchy, respectively. Collectively, these results demonstrate that measures of the principal FC gradient, especially derived using GFC, effectively capture a reliable feature of the human brain subject to interpretable and biologically meaningful individual variation, offering some advantages over traditional edge-wise FC measures in the search for brain-behavior associations.

Introducing Quin: The design and development of a prototype chatbot to support smoking cessation.

INTRODUCTION: Chatbots emulate human-like interactions and may usefully provide on-demand access to tailored smoking cessation support. We have developed a prototype smartphone application-based smoking cessation chatbot, named Quin, grounded in real-world, evidence- and theory-based smoking cessation counselling sessions. METHOD: Conversation topics and interactions in Quitline counselling sessions (N=30; 18 hours) were characterised using thematic, content, and proponent analyses of transcripts. Quin was created by programming this content using a chatbot framework which interacts with users via speech-to-text. Reiterative changes and additions were made to the conversation structure and dialogue following regular consultation with a multidisciplinary team from relevant fields, and from evidence-based resources. RESULTS: Chatbot conversations were encoded into initial and scheduled follow-up 'appointments'. Collection of demographic information, and smoking and quit history, informed tailored discussion about pharmacotherapy preferences, behavioural strategies, and social and professional support to form a quit plan. Follow-up appointments were programmed to check in on user progress, review elements of the quit plan, answer questions and solve issues. Quin was programmed to include teachable moments and educational content to enhance health literacy and informed decision-making. Personal agency is encouraged through exploration and self-reflection of users' personal behaviours, experiences, preferences and ideas. CONCLUSION: Quin's successful development represents a movement towards improving access to personalised smoking cessation support. Qualitative foundations of Quin provide greater insight into the smoking cessation counselling relationship and enhances the conversational ability of the technology. The prototype chatbot will be refined through beta-testing with end-users and stakeholders prior to evaluation in a clinical trial. IMPLICATIONS: Our novel study provides transparent description of the translation of qualitative evidence of real-world smoking cessation counselling sessions into the design and development of a prototype smoking cessation chatbot. The successful iterative development of Quin not only embodies the science and art of health promotion, but also a step-forward in expanding the reach of tailored, evidence based, in-pocket support for people who want to quit smoking.

Replicability of structural brain alterations associated with general psychopathology: evidence from a population-representative birth cohort.

Transdiagnostic research has identified a general psychopathology factor-often called the 'p' factor-that accounts for shared variation across internalizing, externalizing, and thought disorders in diverse samples. It has been argued that the p factor may reflect dysfunctional thinking present in serious mental illness. In support of this, we previously used a theory-free, data-driven multimodal neuroimaging approach to find that higher p factor scores are associated with structural alterations within a cerebello-thalamo-cortical circuit (CTCC) and visual association cortex, both of which are important for monitoring and coordinating information processing in the service of executive control. Here we attempt to replicate these associations by conducting region-of-interest analyses using data from 875 members of the Dunedin Longitudinal Study, a five-decade study of a population-representative birth cohort, collected when they were 45 years old. We further sought to replicate a more recent report that p factor scores can be predicted by patterns of distributed cerebellar morphology as estimated through independent component analysis. We successfully replicated associations between higher p factor scores and both reduced gray matter volume of the visual association cortex and fractional anisotropy of pontine white matter pathways within the CTCC. In contrast, we failed to replicate prior associations between cerebellar structure and p factor scores. Collectively, our findings encourage further focus on the CTCC and visual association cortex as core neural substrates and potential biomarkers of general psychopathology.

Brain-age in midlife is associated with accelerated biological aging and cognitive decline in a longitudinal birth cohort.

An individual's brainAGE is the difference between chronological age and age predicted from machine-learning models of brain-imaging data. BrainAGE has been proposed as a biomarker of age-related deterioration of the brain. Having an older brainAGE has been linked to Alzheimer's, dementia, and mortality. However, these findings are largely based on cross-sectional associations which can confuse age differences with cohort differences. To illuminate the validity of brainAGE as a biomarker of accelerated brain aging, a study is needed of a large cohort all born in the same year who nevertheless vary on brainAGE. In the Dunedin Study, a population-representative 1972-73 birth cohort, we measured brainAGE at age 45 years, as well as the pace of biological aging and cognitive decline in longitudinal data from childhood to midlife (N = 869). In this cohort, all chronological age 45 years, brainAGE was measured reliably (ICC = 0.81) and ranged from 24 to 72 years. Those with older midlife brainAGEs tended to have poorer cognitive function in both adulthood and childhood, as well as impaired brain health at age 3. Furthermore, those with older brainAGEs had an accelerated pace of biological aging, older facial appearance, and early signs of cognitive decline from childhood to midlife. These findings help to validate brainAGE as a potential surrogate biomarker for midlife intervention studies that seek to measure dementia-prevention efforts in midlife. However, the findings also caution against the assumption that brainAGE scores represent only age-related deterioration of the brain as they may also index central nervous system variation present since childhood.

What Do People Want in a Smoking Cessation App? An Analysis of User Reviews and App Quality.

INTRODUCTION: Mobile smoking cessation (mCessation) apps have the potential to complement and enhance existing interventions, but many are of low quality. Exploring app reviews can provide a broader understanding of user experiences and engagement, to enhance the quality, acceptability, and effectiveness of future developments. METHODS: Publicly available user reviews and ratings of smoking cessation apps were mined from Google Play and the App Store via a targeted two-stage search strategy. English language smoking cessation apps with at least 20 consumer reviews between 2011 and 2020 were included. User reviews were thematically analyzed using Braun and Clarke's framework. Apps were independently scored using the Mobile Apps Rating Scale (MARS) and compared to average user star ratings. RESULTS: Forty-eight versions of 42 apps, encompassing 1414 associated reviews, met eligibility criteria. Inductive coding of reviews produced 1084 coding references including reviews coded across multiple nodes. Themes generated included: (1) supportive characteristics/tools; (2) useability; (3) influence on smoking behavior; (4) benefits of quitting; and (5) role as a supplementary tool for quitting. The mean MARS score of 36 free and accessible apps was 3.10 (SD 0.71) with mean scores ranging from 2.00 to 4.47. An inverse relationship between MARS scores and average user star ratings was observed. CONCLUSIONS: App personalization, relationality, functionality, and credibility were important to users, and should be considered as key design components for future apps. Differences between user star ratings and MARS scores may illustrate competing priorities of consumers and researchers, and the importance of a codesign development method. IMPLICATIONS: This is the first study to use unsolicited user reviews from a large population to understand the general mCessation user experience in relation to making a quit attempt. Our findings highlight specific features favored and disliked by users, including their influence on engagement, and supports previous findings that mCessation applications need to be highly tailorable, functional, credible, and supportive. We recommend a consumer-driven, co-design approach for future mCessation app developments to optimize user acceptability and engagement.

Association of subcortical gray-matter volumes with life-course-persistent antisocial behavior in a population-representative longitudinal birth cohort.

Neuropsychological evidence supports the developmental taxonomy theory of antisocial behavior, suggesting that abnormal brain development distinguishes life-course-persistent from adolescence-limited antisocial behavior. Recent neuroimaging work confirmed that prospectively-measured life-course-persistent antisocial behavior is associated with differences in cortical brain structure. Whether this extends to subcortical brain structures remains uninvestigated. This study compared subcortical gray-matter volumes between 672 members of the Dunedin Study previously defined as exhibiting life-course-persistent, adolescence-limited or low-level antisocial behavior based on repeated assessments at ages 7-26 years. Gray-matter volumes of 10 subcortical structures were compared across groups. The life-course-persistent group had lower volumes of amygdala, brain stem, cerebellum, hippocampus, pallidum, thalamus, and ventral diencephalon compared to the low-antisocial group. Differences between life-course-persistent and adolescence-limited individuals were comparable in effect size to differences between life-course-persistent and low-antisocial individuals, but were not statistically significant due to less statistical power. Gray-matter volumes in adolescence-limited individuals were near the norm in this population-representative cohort and similar to volumes in low-antisocial individuals. Although this study could not establish causal links between brain volume and antisocial behavior, it constitutes new biological evidence that all people with antisocial behavior are not the same, supporting a need for greater developmental and diagnostic precision in clinical, forensic, and policy-based interventions.

What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis.

Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task functional MRI (fMRI) is a major focus of biomarker development; however, the reliability of task fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N = 1,008) revealed poor overall reliability-mean intraclass correlation coefficient (ICC) = .397. Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected by the Human Connectome Project (N = 45) and the Dunedin Study (N = 20) were poor (ICCs = .067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or for individual-differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.

A Polygenic Score for Higher Educational Attainment is Associated with Larger Brains.

People who score higher on intelligence tests tend to have larger brains. Twin studies suggest the same genetic factors influence both brain size and intelligence. This has led to the hypothesis that genetics influence intelligence partly by contributing to the development of larger brains. We tested this hypothesis using four large imaging genetics studies (combined N = 7965) with polygenic scores derived from a genome-wide association study (GWAS) of educational attainment, a correlate of intelligence. We conducted meta-analysis to test associations among participants' genetics, total brain volume (i.e., brain size), and cognitive test performance. Consistent with previous findings, participants with higher polygenic scores achieved higher scores on cognitive tests, as did participants with larger brains. Participants with higher polygenic scores also had larger brains. We found some evidence that brain size partly mediated associations between participants' education polygenic scores and their cognitive test performance. Effect sizes were larger in the population-based samples than in the convenience-based samples. Recruitment and retention of population-representative samples should be a priority for neuroscience research. Findings suggest promise for studies integrating GWAS discoveries with brain imaging to understand neurobiology linking genetics with cognitive performance.

Association of Childhood Lead Exposure With MRI Measurements of Structural Brain Integrity in Midlife.

Importance: Childhood lead exposure has been linked to disrupted brain development, but long-term consequences for structural brain integrity are unknown. Objective: To test the hypothesis that childhood lead exposure is associated with magnetic resonance imaging (MRI) measurements of lower structural integrity of the brain in midlife. Design, Setting, and Participants: The Dunedin Study followed a population-representative 1972-1973 birth cohort in New Zealand (N = 564 analytic sample) to age 45 years (until April 2019). Exposures: Childhood blood lead levels measured at age 11 years. Main Outcomes and Measures: Structural brain integrity at age 45 years assessed via MRI (primary outcomes): gray matter (cortical thickness, surface area, hippocampal volume), white matter (white matter hyperintensities, fractional anisotropy [theoretical range, 0 {diffusion is perfectly isotropic} to 100 {diffusion is perfectly anisotropic}]), and the Brain Age Gap Estimation (BrainAGE), a composite index of the gap between chronological age and a machine learning algorithm-estimated brain age (0 indicates a brain age equivalent to chronological age; positive and negative values represent an older and younger brain age, respectively). Cognitive function at age 45 years was assessed objectively via the Wechsler Adult Intelligence Scale IV (IQ range, 40-160, standardized to a mean of 100 [SD, 15]) and subjectively via informant and self-reports (z-score units; scale mean, 0 [SD, 1]). Results: Of 1037 original participants, 997 were alive at age 45 years, of whom 564 (57%) had received lead testing at age 11 years (302 [54%] male) (median follow-up, 34 [interquartile range, 33.7-34.7] years). Mean blood lead level at age 11 years was 10.99 (SD, 4.63) µg/dL. After adjusting for covariates, each 5-µg/dL higher childhood blood lead level was significantly associated with 1.19-cm2 smaller cortical surface area (95% CI, -2.35 to -0.02 cm2; P = .05), 0.10-cm3 smaller hippocampal volume (95% CI, -0.17 to -0.03 cm3; P = .006), lower global fractional anisotropy (b = -0.12; 95% CI, -0.24 to -0.01; P = .04), and a BrainAGE index 0.77 years older (95% CI, 0.02-1.51 years; P = .05) at age 45 years. There were no statistically significant associations between blood lead level and log-transformed white matter hyperintensity volume (b = 0.05 log mm3; 95% CI, -0.02 to 0.13 log mm3; P = .17) or mean cortical thickness (b = -0.004 mm; 95% CI, -0.012 to 0.004 mm; P = .39). Each 5-µg/dL higher childhood blood lead level was significantly associated with a 2.07-point lower IQ score at age 45 years (95% CI, -3.39 to -0.74; P = .002) and a 0.12-point higher score on informant-rated cognitive problems (95% CI, 0.01-0.23; P = .03). There was no statistically significant association between childhood blood lead levels and self-reported cognitive problems (b = -0.02 points; 95% CI, -0.10 to 0.07; P = .68). Conclusions and Relevance: In this longitudinal cohort study with a median 34-year follow-up, higher childhood blood lead level was associated with differences in some MRI measures of brain structure that suggested lower structural brain integrity in midlife. Because of the large number of statistical comparisons, some findings may represent type I error.

General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks.

Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.

Novel muon imaging techniques.

Owing to the high penetrating power of high-energy cosmic ray muons, muon imaging techniques can be used to image large bulky objects, especially objects with heavy shielding. Muon imaging systems work just like CT scanners in the medical imaging field-that is, they can reveal information inside of a target. There are two forms of muon imaging techniques: muon absorption imaging and muon multiple scattering imaging. The former is based on the flux attenuation of muons, and the latter is based on the multiple scattering of muons in matter. The muon absorption imaging technique is capable of imaging very large objects such as volcanoes and large buildings, and also smaller objects like spent fuel casks; the muon multiple scattering imaging technique is best suited to inspect smaller objects such as nuclear waste containers. Muon imaging techniques can be applied in a broad variety of fields, i.e. from measuring the magma thickness of volcanoes to searching for secret cavities in pyramids, and from monitoring the borders of countries checking for special nuclear materials to monitoring the spent fuel casks for nuclear safeguards applications. In this paper, the principles of muon imaging are reviewed. Image reconstruction algorithms such as Filtered Back Projection and Maximum Likelihood Expectation Maximization are discussed. The capability of muon imaging techniques is demonstrated through a Geant4 simulation study for imaging a nuclear spent fuel cask.This article is part of the Theo Murphy meeting issue 'Cosmic-ray muography'.

First-of-a-kind muography for nuclear waste characterization.

In the last decade, there has been a surge in the number of academic research groups and commercial companies exploiting naturally occurring cosmic-ray muons for imaging purposes in a range of industrial and geological applications. Since 2009, researchers at the University of Glasgow and the UK National Nuclear Laboratory (NNL) have pioneered this technique for the characterization of shielded nuclear waste containers with significant investment from the UK Nuclear Decommissioning Authority and Sellafield Ltd. Lynkeos Technology Ltd. was formed in 2016 to commercialize the Muon Imaging System (MIS) technology that resulted from this industry-funded academic research. The design, construction and performance of the Lynkeos MIS is presented along with first experimental and commercial results. The high-resolution images include the identification of small fragments of uranium within a surrogate 500-litre intermediate level waste container and metal inclusions within thermally treated GeoMelt® R&D Product Samples. The latter of these are from Lynkeos' first commercial contract with the UK National Nuclear Laboratory. The Lynkeos MIS will be deployed at the NNL Central Laboratory facility on the Sellafield site in Summer 2018 where it will embark upon a series of industry trials.This article is part of the Theo Murphy meeting issue 'Cosmic-ray muography'.

Parallel-Forms Reliability and Clinical Utility of an Application Version of the Activity Card Sort Australia (18-64).

OBJECTIVE: This study examined the parallel-forms reliability of a web application (app) of the Activity Card Sort Australia for adults ages 18-64 and assessed its clinical utility. METHOD: Forty-eight participants completed the app and card versions of the tool within a 2- to 3-wk interval and provided feedback via a purpose-designed survey. Intraclass correlation analysis tested parallel-forms reliability. RESULTS: The app demonstrated acceptable parallel-forms reliability for overall retained activity level (r = .75, p < .001), the daily life domain (r = .77, p < .001), and the recreation and relaxation domain (r = .74, p < .001), but not for the physical activity domain (r = .59, p < .001). Clinical utility responses suggested good acceptance of both versions. CONCLUSION: The results suggest that further studies are required before the app version can be used for research or in clinical settings.

Can smartphones measure momentary quality of life and participation? A proof of concept using experience sampling surveys with university students.

BACKGROUND: Understanding quality of life and participation is a key aspect of occupational therapy research. The use of smartphones to deliver experience-sampling surveys may provide an accessible way to monitor these outcomes. This study used smartphone-based experience sampling methods (ESM) to investigate factors influencing momentary quality of life (mQOL) of university students. METHODS: A convenience sample of students at an Australian university participated. Using a custom smartphone application, ESM surveys were sent six to eight times, every second day, over a week. Participants indicated their mQOL, occupational participation, occupational enjoyment, social context and location via surveys and provided demographic and health information in a single self-report questionnaire. The relationship between mQOL and variables was analysed at the survey level using logistic regression. RESULTS: Forty students completed 391 surveys. Higher mQOL was significantly related to participation in productive occupations (z = 3.48; P = 0.001), moderate (z = 4.00; P < 0.001) or high occupational enjoyment (z = 7.06; P < 0.001), being with someone (z = 2.15, P = 0.031), being at home (z = 2.49; P = 0.013) and an excellent self-rated health status (z = 2.35; P = 0.019). The magnitude of differences in mQOL was small. CONCLUSION: This study suggests that mQOL amongst university students relates to personal, environmental and occupational factors. The use of smartphone-based ESM appears to be a practical approach for investigating participation and QOL. Further research utilising a more diverse sample, analysing at the individual level, and using ESM in conjunction with other methodologies is recommended.

Balancing Self-Tracking and Surveillance: Legal, Ethical and Technological Issues in Using Smartphones to Monitor Communication in People with Health Conditions.

Smartphones are being used to track the health of individuals in their own environments. For example, a smartphone app could be used to monitor the impact and progression of Parkinson's disease, as well as indicate whether treatments may need to be adjusted, based on an analysis of voice and discourse. The app uses smartphone audio sensors to detect when conversations are taking place and activates an app to record the conversation. But what happens if a background conversation is also collected by the recording? The participants of the background conversation are unaware of and have not consented to the recording. Unauthorised recording could also raise legal issues under surveillance devices legislation and has ethical implications. It is a complex task to balance the potential benefits of self-tracking of health conditions to consumers and the health system, with the legalities and ethical issues related to privacy. The health-related monitoring industry is moving so rapidly that current legal and ethical processes and protocols may fail to balance these concerns. This article explores Australian legal and ethical perspectives on how to achieve the potential benefits of these technological approaches while preserving privacy.