Visuo-spatial ability in colonoscopy simulator training

Visuo-spatial ability is associated with a quality of performance in a variety of surgical and medical skills. However, visuo-spatial ability is typically assessed using Visualization tests only, which led to an incomplete understanding of the involvement of visuo-spatial ability in these skills. To remedy this situation, the current study investigated the role of a broad range of visuo-spatial factors in colonoscopy simulator training. Fifteen medical trainees (no clinical experience in colonoscopy) participated in two psycho-metric test sessions to assess four visuo-spatial ability factors. Next, participants trained flexible endoscope manipulation, and navigation to the cecum on the GI Mentor II simulator, for four sessions within 1 week. Visualization, and to a lesser degree Spatial relations were the only visuo-spatial ability factors to correlate with colonoscopy simulator performance. Visualization additionally covaried with learning rate for time on task on both simulator tasks. High Visualization ability indicated faster exercise completion. Similar to other endoscopic procedures, performance in colonoscopy is positively associated with Visualization, a visuo-spatial ability factor characterized by the ability to mentally manipulate complex visuo-spatial stimuli. The complexity of the visuo-spatial mental transformations required to successfully perform colonoscopy is likely responsible for the challenging nature of this technique, and should inform training- and assessment design. Long term training studies, as well as studies investigating the nature of visuo-spatial complexity in this domain are needed to better understand the role of visuo-spatial ability in colonoscopy, and other endoscopic techniques

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

Anti-SARS-CoV2 antibody responses in serum and cerebrospinal fluid of COVID-19 patients with neurological symptoms

Antibody responses to SARS-CoV-2 in serum and CSF from 16 COVID-19 patients with neurological symptoms were assessed using two independent methods. IgG specific for the virus spike protein was found in 81% of cases in serum and in 56% in CSF. SARS-CoV-2 IgG in CSF was observed in two cases with negative serology. Levels of IgG in both serum and CSF were associated with disease severity (p<0.05). All patients with elevated markers of CNS damage in CSF also had CSF antibodies (p=0.002), and CSF antibodies had the highest predictive value for neuronal damage markers of all tested clinical variables

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

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

Immigration and recommended care after a suicide attempt in Europe: equity or bias?

This report describes the investigation of care recommendations in the medical system across European countries to immigrants who attempted suicide. Data from seven European countries with 8865 local and 2921 immigrant person-cases were derived from the WHO/EURO Multicentre Study on Suicidal Behaviour and ensuing MONSUE (Monitoring Suicidal Behaviour in Europe) project. The relationship between immigrant status and type of aftercare recommended was analysed with binary logistic regression, adjusting for gender, age, method of attempt and the Centre collecting the data. Clear disparities were identified in the care recommendation practices toward immigrants, compared with hosts, over and above differing policies by the European Centres

Investigating dietary life histories and mobility of children buried in St Gertrude Church Cemetery, Riga, Latvia (15th– 17th centuries AD)

Carbon and nitrogen isotope profiles were obtained from incremental dentine analysis of 19 non‐adults from a cemetery in Riga, Latvia. The research compared the life histories and diet between people buried in two mass graves and the general cemetery. The δ13C profiles of several children from the mass graves were similar but did not resemble the patterns seen in children from the general cemetery, suggesting that they probably represented a different population group. The rise in δ15N values towards the end of the life of four individuals from one mass grave suggests they were victims of an historically documented famine

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

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

Plasma based markers of [11C] PiB-PET brain amyloid burden.

PublishedJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tChanges in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [(11)C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden--c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E--were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE [Symbol: see text] 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.Alzheimer's Disease Neuroimaging Initiative (ADNI)Canadian Institutes of Health ResearchFoundation for the National Institutes of HealthNational Institutes of HealthInnoMed, European Union of the Sixth Framework programNational Institutes for Health Research Biomedical Research Centre for Mental Health at the South London and Maudsley National Health Service Foundation TrustInstitute of Psychiatry, King's College Londo