Mental Health of Parents and Life Satisfaction of Children: A Within-Family Analysis of Intergenerational Transmission of Well-Being

This paper addresses the extent to which there is an intergenerational transmission of mental health and subjective well-being within families. Specifically it asks whether parents’ own mental distress influences their child’s life satisfaction, and vice versa. Whilst the evidence on daily contagion of stress and strain between members of the same family is substantial, the evidence on the transmission between parental distress and children’s well-being over a longer period of time is sparse. We tested this idea by examining the within-family transmission of mental distress from parent to child’s life satisfaction, and vice versa, using rich longitudinal data on 1,175 British youths. Results show that parental distress at year t-1 is an important determinant of child’s life satisfaction in the current year. This is true for boys and girls, although boys do not appear to be affected by maternal distress levels. The results also indicated that the child’s own life satisfaction is related with their father’s distress levels in the following year, regardless of the gender of the child. Finally, we examined whether the underlying transmission correlation is due to shared social environment, empathic reactions, or transmission via parent-child interaction

The extent of neuroradiological findings in COVID-19 shows correlation with blood biomarkers, Glasgow coma scale score and days in intensive care

Background and purpose: A wide range of neuroradiological findings has been reported in patients with coronavirus disease 2019 (COVID-19), ranging from subcortical white matter changes to infarcts, haemorrhages and focal contrast media enhancement. These have been descriptively but inconsistently reported and correlations with clinical findings and biomarkers have been difficult to extract from the literature. The purpose of this study was to quantify the extents of neuroradiological findings in a cohort of patients with COVID-19 and neurological symptoms, and to investigate correlations with clinical findings, duration of intensive care and biomarkers in blood. Material and methods: Patients with positive SARS-CoV-2 and at least one new-onset neurological symptom were included from April until July 2020. Nineteen patients were examined regarding clinical symptoms, biomarkers in blood and MRI of the brain. In order to quantify the MRI findings, a semi-quantitative neuroradiological severity scale was constructed a priori, and applied to the MR images by two specialists in neuroradiology. Results and conclusions: The score from the severity scale correlated significantly with blood biomarkers of CNS injury (glial fibrillary acidic protein, total-tau, ubiquitin carboxyl-terminal hydrolase L1) and inflammation (C-reactive protein), Glasgow Coma Scale score, and the number of days spent in intensive care. The underlying radiological assessments had inter-rater agreements of 90.5%/86% (for assessments with 2/3 alternatives). Total intraclass correlation was 0.80. Previously reported neuroradiological findings in COVID-19 have been diverse and heterogenous. In this study, the extent of findings in MRI examination of the brain, quantified using a structured report, shows correlation with relevant biomarkers

Biomarkers for CNS injury in CSF are elevated in COVID-19 and associated with neurological symptoms and disease severity

BACKGROUND: Neurological symptoms have been frequently reported in hospitalized patients with coronavirus disease 2019 (COVID-19) and biomarkers of CNS injury are reported to be increased in plasma but not extensively studied in CSF. This study examines CSF for biomarkers of CNS injury and other pathology in relation to neurological symptoms and disease severity in patients with neurological manifestations of COVID-19. METHODS: Nineteen patients with neurological symptoms and mild to critical COVID-19 were prospectively included. Extensive analysis of CSF, including measurement of biomarkers of CNS injury (neurofilament light chain protein (NfL) glial fibrillary acidic protein (GFAp) and total tau) was performed and related to neurological features and disease severity. RESULTS: Neurological symptoms included altered mental status (42%), headache (42%), central (21%) and peripheral weakness (32%). Two patients demonstrated minor pleocytosis and four patients had increased immunoglobulin G levels in CSF. Neuronal autoantibody testing using commercial tests was negative in all patients. Increased CSF levels of NfL, GFAp and total-tau protein were seen in 63%, 37%, and 16% of patients, respectively. Increased NfL correlated with disease severity, time in intensive care and level of consciousness. NfL in CSF was higher in patients with central neurological symptoms. CONCLUSION: Although limited by small sample size, our data suggest that levels of NfL, GFAp and total tau in CSF are commonly elevated in patients with COVID-19 with neurological symptoms. This is in contrast to the standard CSF work-up where pathological findings are scarce. NfL in particular, is associated with central neurological symptoms and disease severity

Particle detectors, geodesic motion, and the equivalence principle

It is shown that quantum particle detectors are not reliable probes of spacetime structure. In particular, they fail to distinguish between inertial and non-inertial motion in a general spacetime. To prove this, we consider detectors undergoing circular motion in an arbitrary static spherically symmetric spacetime, and give a necessary and sufficient condition for the response function to vanish when the field is in the static vacuum state. By examining two particular cases, we show that there is no relation, in general, between the vanishing of the response function and the fact that the detector motion is, or is not, geodesic. In static asymptotically flat spacetimes, however, all rotating detectors are excited in the static vacuum. Thus, in this particular case the static vacuum appears to be associated with a non-rotating frame. The implications of these results for the equivalence principle are considered. In particular, we discuss how to properly formulate the principle for particle detectors, and show that it is satisfied.Comment: 14 pages. Revised version, with corrections; added two references. Accepted for publication in Class. Quantum Gra

Rapid reduction versus abrupt quitting for smokers who want to stop soon: a randomised controlled non-inferiority trial

Background: The standard way to stop smoking is to stop abruptly on a quit day with no prior reduction in consumption of cigarettes. Many smokers feel that reduction is natural and if reduction programmes were offered, many more might take up treatment. Few trials of reduction versus abrupt cessation have been completed. Most are small, do not use pharmacotherapy, and do not meet the standards necessary to obtain a marketing authorisation for a pharmacotherapy.\ud Design/Methods: We will conduct a non-inferiority andomised trial of rapid reduction versus standard abrupt cessation among smokers who want to stop smoking. In the reduction arm,participants will be advised to reduce smoking consumption by half in the first week and to 25% of baseline in the second, leading up to a quit day at which participants will stop smoking completely.This will be assisted by nicotine patches and an acute form of nicotine replacement therapy. In the abrupt arm participants will use nicotine patches only, whilst smoking as normal, for two weeks prior to a quit day, at which they will also stop smoking completely. Smokers in either arm will have standard withdrawal orientated behavioural support programme with a combination of nicotine patches and acute nicotine replacement therapy post-cessation.\ud Outcomes/Follow-up: The primary outcome of interest will be prolonged abstinence from smoking, with secondary trial outcomes of point prevalence, urges to smoke and withdrawal\ud symptoms. Follow up will take place at 4 weeks, 8 weeks and 6 months post-quit day

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type.Comment: Accepted for the Shape in Medical Imaging (ShapeMI) workshop at MICCAI International Conference 202

Reciprocal relations between workplace bullying, anxiety and vigor: A two-wave longitudinal study

Background and Objectives: Workplace bullying has been classified as an extreme social stressor in work contexts and has been repeatedly linked to several negative consequences. However, little research has examined reversed or reciprocal relations of bullying and outcomes. Design: We conducted a two-wave longitudinal study with a time lag of six months. Methods: The study sample consisted of 348 employees of the Spanish workforce. The present study examined longitudinal relationships between workplace bullying, psychological health, and well-being. On the basis of conservation of resources theory, we hypothesized that we would find reciprocal relations among study variables over time. Results: Results of cross-lagged structural equation modeling analyses supported our hypotheses. Specifically, it was found that Time 1 (T1) workplace bullying was negatively related to Time 2 (T2) vigor and positively related to T2 anxiety. Additionally, T1 anxiety and vigor had an effect on T2 workplace bullying. Conclusions: Overall, these findings support the validity of the theoretical models postulating a reciprocal bullying–outcome relationship, rather than simple one-way causal pathways approaches

Automatic ROI Selection in Structural Brain MRI Using SOM 3D Projection

This paper presents a method for selecting Regions of Interest (ROI) in brain Magnetic Resonance Imaging (MRI) for diagnostic purposes, using statistical learning and vector quantization techniques. The proposed method models the distribution of GM and WM tissues grouping the voxels belonging to each tissue in ROIs associated to a specific neurological disorder. Tissue distribution of normal and abnormal images is modelled by a Self-Organizing map (SOM), generating a set of representative prototypes, and the receptive field (RF) of each SOM prototype defines a ROI. Moreover, the proposed method computes the relative importance of each ROI by means of its discriminative power. The devised method has been assessed using 818 images from the Alzheimer's disease Neuroimaging Initiative (ADNI) which were previously segmented through Statistical Parametric Mapping (SPM). The proposed algorithm was used over these images to parcel ROIs associated to the Alzheimer's Disease (AD). Additionally, this method can be used to extract a reduced set of discriminative features for classification, since it compresses discriminative information contained in the brain. Voxels marked by ROIs which were computed using the proposed method, yield classification results up to 90% of accuracy for controls (CN) and Alzheimer's disease (AD) patients, and 84% of accuracy for Mild Cognitive Impairment (MCI) and AD patients.This work was partly supported by the MICINN under the TEC2012-34306 project and the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía, Spain) under the Excellence Projects P09-TIC-4530 and P11-TIC-7103. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRxResearch; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California

Determining Remaining Useful Life of Aging Cables in Nuclear Power Plants ? Interim Study FY13

The most important criterion for cable performance is its ability to withstand a design-basis accident. With nearly 1000 km of power, control, instrumentation, and other cables typically found in an NPP, it would be a significant undertaking to inspect all of the cables. Degradation of the cable jacket, electrical insulation, and other cable components is a key issue that is likely to affect the ability of the currently installed cables to operate safely and reliably for another 20 to 40 years beyond the initial operating life. The development of one or more nondestructive evaluation (NDE) techniques and supporting models that could assist in determining the remaining life expectancy of cables or their current degradation state would be of significant interest. The ability to nondestructively determine material and electrical properties of cable jackets and insulation without disturbing the cables or connections has been deemed essential. Currently, the only technique accepted by industry to measure cable elasticity (the gold standard for determining cable insulation degradation) is the indentation measurement. All other NDE techniques are used to find flaws in the cable and do not provide information to determine the current health or life expectancy. There is no single NDE technique that can satisfy all of the requirements needed for making a life-expectancy determination, but a wide range of methods have been evaluated for use in NPPs as part of a continuous evaluation program. The commonly used methods are indentation and visual inspection, but these are only suitable for easily accessible cables. Several NDE methodologies using electrical techniques are in use today for flaw detection but there are none that can predict the life of a cable. There are, however, several physical and chemical ptoperty changes in cable insulation as a result of thermal and radiation damage. In principle, these properties may be targets for advanced NDE methods to provide early warning of aging and degradation. Examples of such key indicators include changes in chemical structure, mechanical modulus, and dielectric permittivity. While some of these indicators are the basis of currently used technologies, there is a need to increase the volume of cable that may be inspected with a single measurement, and if possible, to develop techniques for in-situ inspection (i.e., while the cable is in operation). This is the focus of the present report