1,681 research outputs found

    A novel concentrated solar membrane-distillation for water purification in a building integrated design

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    Solar-assisted Vacuum Membrane-Distillation provides a lower-energy alternative to water treatment, particularly desalination in dry areas. While horizontally integrated (roof-top) decentralized treatment systems exist, vertically integrated (balcony) water treatment systems remain unexplored. This study improves upon a previous solar-VMD system with a compound parabolic collector and integrate it onto the vertical faces of a building. The novel VMD system generates a flux of >8 L water per square meter of membrane area per hour when operating at a temperature above 65 °C and with a 15 kPa vacuum pressure during peak solar conditions (>800 W/m2). This system's performance was identical under clean-water and desalination operating modes, reinforcing the use-case of urban desalination. Furthermore, a numerical model was developed and validated to be utilized for parametric study. Finally, an economic analysis has shown that the system has a levelized cost of water of 21.5 USD/m3, with the cogeneration of heat via hot water (i.e., a levelized cost of heat of 0.015 USD/kWh) off-setting costs. Assuming a use-case of rural implementation whereby water transport costs dominate, the payback period of the design is around 2 years. Ultimately, this demonstrates a viable decentralized water treatment/hot-water system that can alleviate water scarcity in arid areas

    Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change.

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    Cerebral small vessel disease (SVD) is the primary cause of vascular cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related changes in a single unitary score across the whole cerebrum, to investigate its relationship with cognitive change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to change in EF and IPS (p < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of change in EF and IPS in the multivariate models (p = 0.002). Change in DSEG θ was also related to change in all other MRI markers (p < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain change in SVD that has a negative impact on cognition and remains a significant predictor of cognitive change when other MRI markers of brain change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural changes and successfully predicts cognitive change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs)

    The conceptualisation and measurement of DSM-5 Internet Gaming Disorder: the development of the IGD-20 Test

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    Background: Over the last decade, there has been growing concern about ‘gaming addiction’ and its widely documented detrimental impacts on a minority of individuals that play excessively. The latest (fifth) edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5) included nine criteria for the potential diagnosis of Internet Gaming Disorder (IGD) and noted that it was a condition that warranted further empirical study. Aim: The main aim of this study was to develop a valid and reliable standardised psychometrically robust tool in addition to providing empirically supported cut-off points. Methods: A sample of 1003 gamers (85.2% males; mean age 26 years) from 57 different countries were recruited via online gaming forums. Validity was assessed by confirmatory factor analysis (CFA), criterion-related validity, and concurrent validity. Latent profile analysis was also carried to distinguish disordered gamers from non-disordered gamers. Sensitivity and specificity analyses were performed to determine an empirical cut-off for the test. Results: The CFA confirmed the viability of IGD-20 Test with a six-factor structure (salience, mood modification, tolerance, withdrawal, conflict and relapse) for the assessment of IGD according to the nine criteria from DSM-5. The IGD-20 Test proved to be valid and reliable. According to the latent profile analysis, 5.3% of the total participants were classed as disordered gamers. Additionally, an optimal empirical cut-off of 71 points (out of 100) seemed to be adequate according to the sensitivity and specificity analyses carried

    Mechanisms of Cognitive Impairment in Cerebral Small Vessel Disease: Multimodal MRI Results from the St George's Cognition and Neuroimaging in Stroke (SCANS) Study.

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    Cerebral small vessel disease (SVD) is a common cause of vascular cognitive impairment. A number of disease features can be assessed on MRI including lacunar infarcts, T2 lesion volume, brain atrophy, and cerebral microbleeds. In addition, diffusion tensor imaging (DTI) is sensitive to disruption of white matter ultrastructure, and recently it has been suggested that additional information on the pattern of damage may be obtained from axial diffusivity, a proposed marker of axonal damage, and radial diffusivity, an indicator of demyelination. We determined the contribution of these whole brain MRI markers to cognitive impairment in SVD. Consecutive patients with lacunar stroke and confluent leukoaraiosis were recruited into the ongoing SCANS study of cognitive impairment in SVD (n = 115), and underwent neuropsychological assessment and multimodal MRI. SVD subjects displayed poor performance on tests of executive function and processing speed. In the SVD group brain volume was lower, white matter hyperintensity volume higher and all diffusion characteristics differed significantly from control subjects (n = 50). On multi-predictor analysis independent predictors of executive function in SVD were lacunar infarct count and diffusivity of normal appearing white matter on DTI. Independent predictors of processing speed were lacunar infarct count and brain atrophy. Radial diffusivity was a stronger DTI predictor than axial diffusivity, suggesting ischaemic demyelination, seen neuropathologically in SVD, may be an important predictor of cognitive impairment in SVD. Our study provides information on the mechanism of cognitive impairment in SVD

    Sensitivity of the UK clinical practice research datalink to detect neurodevelopmental effects of medicine exposure in utero:comparative analysis of an antiepileptic drug-exposed cohort

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    Introduction: Electronic healthcare data have several advantages over prospective observational studies, but the sensitivity of data on neurodevelopmental outcomes and its comparability with data generated through other methodologies is unknown. Objectives: The objectives of this study were to determine whether data from the UK Clinical Practice Research Datalink (CPRD) produces similar risk estimates to a prospective cohort study in relation to the risk of neurodevelopmental disorders (NDDs) following prenatal antiepileptic drug (AED) exposure. Methods: A cohort of mother–child pairs of women with epilepsy (WWE) was identified in the CPRD and matched to a cohort without epilepsy. The study period ran from 1 January 2000 to 31 March 2007 and children were required to be in the CPRD at age 6 years. AED exposure during pregnancy was determined from prescription data and children with an NDD diagnosis by 6 years were identified from Read clinical codes. The prevalence and risk of NDDs was calculated for mother–child pairs in WWE stratified by AED regimen and for those without epilepsy. Comparisons were made with the results of the prospective Liverpool and Manchester Neurodevelopment Group study which completed assessment on 201 WWE and 214 without epilepsy at age 6 years. Results: In the CPRD, 1018 mother–child pairs to WWE and 6048 to women without epilepsy were identified. The CPRD identified a lower prevalence of NDDs than the prospective study. In both studies, NDDs were more frequently reported in children of WWE than women without epilepsy, although the CPRD risk estimate was lower (2.16 vs. 0.96%, p < 0.001 and 7.46 vs. 1.87%, p = 0.0128). NDD prevalence differed across AED regimens but the CPRD data did not replicate the significantly higher risk of NDDs following in utero monotherapy valproate exposure (adjusted odds ratio [ORadj] 2.02, 95% confidence interval [CI] 0.52–7.86) observed in the prospective study (ORadj 6.05, 95% CI 1.65–24.53). Conclusion: It was possible to identify NDDs in the CPRD; however, the CPRD appears to under-record these outcomes. Larger studies are required to investigate further

    G-CSF Prevents the Progression of Structural Disintegration of White Matter Tracts in Amyotrophic Lateral Sclerosis: A Pilot Trial

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    Background: The hematopoietic protein Granulocyte-colony stimulating factor (G-CSF) has neuroprotective and regenerative properties. The G-CSF receptor is expressed by motoneurons, and G-CSF protects cultured motoneuronal cells from apoptosis. It therefore appears as an attractive and feasible drug candidate for the treatment of amyotrophic lateral sclerosis (ALS). The current pilot study was performed to determine whether treatment with G-CSF in ALS patients is feasible.Methods: Ten patients with definite ALS were entered into a double-blind, placebo-controlled, randomized trial. Patients received either 10 mu g/kg BW G-CSF or placebo subcutaneously for the first 10 days and from day 20 to 25 of the study. Clinical outcome was assessed by changes in the ALS functional rating scale (ALSFRS), a comprehensive neuropsychological test battery, and by examining hand activities of daily living over the course of the study (100 days). The total number of adverse events (AE) and treatment-related AEs, discontinuation due to treatment-related AEs, laboratory parameters including leukocyte, erythrocyte, and platelet count, as well as vital signs were examined as safety endpoints. Furthermore, we explored potential effects of G-CSF on structural cerebral abnormalities on the basis of voxel-wise statistics of Diffusion Tensor Imaging (DTI), brain volumetry, and voxel-based morphometry.Results: Treatment was well-tolerated. No significant differences were found between groups in clinical tests and brain volumetry from baseline to day 100. However, DTI analysis revealed significant reductions of fractional anisotropy (FA) encompassing diffuse areas of the brain when patients were compared to controls. On longitudinal analysis, the placebo group showed significant greater and more widespread decline in FA than the ALS patients treated with G-CSF.Conclusions: Subcutaneous G-CSF treatment in ALS patients appears as feasible approach. Although exploratory analysis of clinical data showed no significant effect, DTI measurements suggest that the widespread and progressive microstructural neural damage in ALS can be modulated by G-CSF treatment. These findings may carry significant implications for further clinical trials on ALS using growth factors

    Self-harm and suicidality experiences of middle-age and older adults with vs. without high autistic traits.

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    This is the final version. Available from Springer via the DOI in this record. Suicide has been identified as a leading cause of premature death in autistic populations. Elevated autistic traits have also been associated with higher rates of self-harm, suicidal ideation, and suicidal self-harm in the general population, but this has yet to be examined in older age. Using baseline cross-sectional data from the PROTECT study, middle-age and older adults with high autistic traits (n = 276) had significantly higher rates of suicidal ideation, deliberate self-harm, and suicidal self-harm than an age/sex-matched comparison group (n = 10,495). These differences represented a 5- to 6-fold increase in likelihood for self-harming and suicidality. These findings, which remained when controlling for depression symptoms, suggest that middle-age and older adults with high autistic traits may be particularly at risk of self-harm and suicidal behaviours.National Institute for Health ResearchEconomic and Social Research Counci

    Traumatic life experiences and post-traumatic stress symptoms in middle-aged and older adults with and without autistic traits

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    Data Availability Statement: The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1002/gps.5669#support-information-section .Copyright © 2022 The Authors. Objectives: Research with younger adults has begun to explore associations between autism/autistic traits and vulnerability to Post Traumatic Stress Disorder (PTSD). Large scale studies and/or examination of age-effects have not been conducted. Methods: Adults aged 50 years+ from the PROTECT study (n = 20,220) completed items about current and childhood socio-communicative difficulties characteristic of autism. Approximately 1% (n = 251) endorsed high autistic traits, henceforth the Autism Spectrum Traits (AST) group. Differences between the AST and an age—and sex-matched “Comparison Older Adults” (COA; n = 9179) group were explored for lifetime traumatic experiences and current symptoms of PTSD, depression, and anxiety. Results: Almost 30% of the AST group, compared to less than 8% of the COA, reported severe trauma in childhood/adulthood, including emotional, physical or sexual abuse. Elevated current PTSD symptoms were reported by AST compared to COA. An interaction was observed between autistic traits and trauma severity; the effect of level of trauma on PTSD symptoms was significantly greater for AST versus COA participants. This interaction remained significant when controlling for current depression and anxiety symptoms. Conclusions: The findings suggest that high autistic traits may increase the likelihood of experiencing trauma across the lifespan, and the impact of severe trauma on PTSD symptoms. Older adults with high (vs. low) autistic traits may be at greater risk of experiencing PTSD symptoms in latter life. Future research should test whether the pattern of results is similar for diagnosed autistic adults.National Institutes of Health Research (NIHR); Economic and Social Research Council

    Prevalence and predictors of video game addiction: a study based on a national representative sample of gamers

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    Video gaming has become a popular leisure activity in many parts of the world, and an increasing number of empirical studies examine the small minority that appears to develop problems as a result of excessive gaming. This study investigated prevalence rates and predictors of video game addiction in a sample of gamers, randomly selected from the National Population Registry of Norway (N =3389). Results showed there were 1.4 % addicted gamers, 7.3 % problem gamers, 3.9 % engaged gamers, and 87.4 % normal gamers. Gender (being male) and age group (being young) were positively associated with addicted-, problem-, and engaged gamers. Place of birth (Africa, Asia, South- and Middle America) were positively associated with addicted- and problem gamers. Video game addiction was negatively associated with conscientiousness and positively associated with neuroticism. Poor psychosomatic health was positively associated with problem- and engaged gaming. These factors provide insight into the field of video game addiction, and may help to provide guidance as to how individuals that are at risk of becoming addicted gamers can be identified

    Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques

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    We evaluated the ability of simple and complex surrogate-indices to identify individuals from an overweight/obese cohort with hepatic insulin-resistance (HEP-IR). Five indices, one previously defined and four newly generated through step-wise linear regression, were created against a single-cohort sample of 77 extensively characterised participants with the metabolic syndrome (age 55.6±1.0 years, BMI 31.5±0.4 kg/m2; 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6–62H2] glucose during fasting and euglycemic-hyperinsulinemic clamps and expressed as EGP*fasting plasma insulin. Complex measures were incorporated into the model, including various non-standard biomarkers and the measurement of body-fat distribution and liver-fat, to further improve the predictive capability of the index. Validation was performed against a data set of the same subjects after an isoenergetic dietary intervention (4 arms, diets varying in protein and fiber content versus control). All five indices produced comparable prediction of HEP-IR, explaining 39–56% of the variance, depending on regression variable combination. The validation of the regression equations showed little variation between the different proposed indices (r2 = 27–32%) on a matched dataset. New complex indices encompassing advanced measurement techniques offered an improved correlation (r = 0.75, P<0.001). However, when validated against the alternative dataset all indices performed comparably with the standard homeostasis model assessment for insulin resistance (HOMA-IR) (r = 0.54, P<0.001). Thus, simple estimates of HEP-IR performed comparable to more complex indices and could be an efficient and cost effective approach in large epidemiological investigations
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