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People with severe neuromuscular trunk impairment cannot maintain or control upright posture of the upper body in sitting while reaching. Passive orthoses are clinically available to provide support and promote the use of upper extremities in this population. However, these orthoses only position the torso passively without any degree of trunk movement.
We introduce for the first time a novel active-assistive torso brace called Wheelchair Robot for Active Postural Support (WRAPS). It consists of two rings over the hips and chest connected by a 2RPS-2UPS parallel robotic device. WRAPS can modulate the displacement of the upper ring and/or the forces applied on the torso through the ring in four degrees-of-freedom (DOF), including rotations and translation in the sagittal and frontal planes.
In the present study, we evaluate the design of WRAPS and its functions. Moreover, we discuss the potential effectiveness of WRAPS as a therapeutic robotic tool in people with severe trunk control deficits. The performance of WRAPS was evaluated in seated healthy subjects. Kinematics and surface electromyography (sEMG) were collected when the participants performed selective trunk movements. First, the torso range of motion (tROM) was calculated with WRAPS in transparent mode—zero-force control mode—which was compared with free-guided tROM (no WRAPS) with motion capture system. Second, a position control mode was configured to mobilize the torso along the trajectories obtained with the transparent mode.
Our results show that the design of WRAPS suited well the subject’s anthropometrics while supporting the weight of the torso. Importantly, WRAPS can be programmed to replicate the subject’s tROM, without the full activation of torso muscles. This can be critical in individuals with no trunk control. Altogether, these preliminary results indicate the potential applicability of WRAPS to promote active-assistive trunk mobility in people who cannot sit independently because of trunk dysfunction.
The growing application of data-driven analytics in materials science has led to the rise of materials informatics. Within the arena of data analytics, deep learning has emerged as a game-changing technique in the last few years, enabling numerous real-world applications, such as self-driving cars. In this paper, the authors present an overview of deep learning, its advantages, challenges, and recent applications on different types of materials data. The increasingly availability of materials databases and big data in general, along with groundbreaking advances in deep learning offers a lot of promise to accelerate the discovery, design, and deployment of next-generation materials.
Functional non-epileptic attacks (FNEA) are seizure-like events occurring in the absence of epilepsy. Having had many different names over the years including dissociative convulsions and pseudo-seizures, they now fall in the borderland between neurology and psychiatry, often not accepted by either specialty. However, there is evidence that there is a high rate of psychiatric comorbidity in these patients and therefore it is likely that psychiatrists will come across patients with FNEA and they should know the broad principles of assessment and management.
We have provided a clinically based overview of the evidence regarding epidemiology, risk factors, clinical features, differentiation from epilepsy, prognosis, assessment and treatment.
By the end of this article, readers should be able to understand the difference between epileptic seizures and FNEA, know how to manage acute FNEA, and understand the principles of neuropsychiatric assessment and management of these patients, based on knowledge of the evidence base.
Informed consent was obtained from the patient for publication of Box 1.
We report the case of a 14-year-old female who had tetralogy of Fallot along with anomalous origin of the left pulmonary artery from the ascending aorta with co-dominant double aortic arch forming a complete vascular ring compressing the oesophagus along with a left main coronary artery to right ventricular outflow tract fistula. She underwent surgical correction without conduit placement.
Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.
Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).
Positive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation.
This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.
Depression is a common, serious, but under-recognised problem in multiple sclerosis (MS). The primary objective of this study was to assess whether a rapid visual analogue screening tool for depression could operate as a quick and reliable screening method for depression, in patients with MS.
Patients attending a regional MS outpatient clinic completed the Emotional Thermometer 7 tool (ET7), the Hospital Anxiety and Depression Scale – Depression Subscale (HADS-D) and the Major Depression Inventory (MDI) to establish a Diagnostic and Statistical Manual, 4th edition (DSM-IV) diagnosis of Major Depression. Full ET7, briefer subset ET4 version and depression and distress thermometers alone were compared with HADS-D and MDI. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and receiver operating characteristic (ROC) curve were calculated to compare the performance of all the screening tools.
In total, 190 patients were included. ET4 performed well as a ‘rule-out’ screening step (sensitivity 0.91, specificity 0.72, NPV 0.98, PPV 0.32). ET4 performance was comparable to HADS-D (sensitivity 0.96, specificity 0.77, NPV 0.99, PPV 0.37) without need for clinician scoring. The briefer ET4 performed as well as the full ET7.
ET are quick, sensitive and useful screening tools for depression in this MS population, to be complemented by further questioning or more detailed psychiatric assessment where indicated. Given that ET4 and ET7 perform equally well, we recommend the use of ET4 as it is briefer. It has the potential to be widely implemented across busy neurology clinics to assist in depression screening in this under diagnosed group.
We present a deep learning approach to the indexing of electron backscatter diffraction (EBSD) patterns. We design and implement a deep convolutional neural network architecture to predict crystal orientation from the EBSD patterns. We design a differentiable approximation to the disorientation function between the predicted crystal orientation and the ground truth; the deep learning model optimizes for the mean disorientation error between the predicted crystal orientation and the ground truth using stochastic gradient descent. The deep learning model is trained using 374,852 EBSD patterns of polycrystalline nickel from simulation and evaluated using 1,000 experimental EBSD patterns of polycrystalline nickel. The deep learning model results in a mean disorientation error of 0.548° compared to 0.652° using dictionary based indexing.
Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders.
We assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia.
Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50.
Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.
Gambling disorder (GD), recognized in Diagnostic and Statistical Manual of Mental Disorders, Version 5 (DSM-5) as a behavioral addiction, is associated with a range of adverse outcomes. However, there has been little research on the genetic and environmental influences on the development of this disorder. This study reports results from the largest twin study of GD conducted to date.
Replication and combined analyses were based on samples of 3292 (mean age 31.8, born 1972–79) and 4764 (mean age 37.7, born 1964–71) male, female, and unlike-sex twin pairs from the Australian Twin Registry. Univariate biometric twin models estimated the proportion of variation in the latent GD liability that could be attributed to genetic, shared environmental, and unique environmental factors, and whether these differed quantitatively or qualitatively for men and women.
In the replication study, when using a lower GD threshold, there was evidence for significant genetic (60%; 95% confidence interval (CI) 45–76%) and unique environmental (40%; 95% CI 24–56%), but not shared environmental contributions (0%; 95% CI 0–0%) to GD liability; this did not significantly differ from the original study. In the combined analysis, higher GD thresholds (such as one consistent with DSM-5 GD) and a multiple threshold definitions of GD yielded similar results. There was no evidence for quantitative or qualitative sex differences in the liability for GD.
Twin studies of GD are few in number but they tell a remarkably similar story: substantial genetic and unique environmental influences, with no evidence for shared environmental contributions or sex differences in GD liability.
Anomalous aortic origin of a coronary artery is the second leading cause of sudden cardiac arrest/death in young athletes in the United States of America. Limited data are available regarding family history in this patient population.
Patients were evaluated prospectively from 12/2012 to 02/2017 in the Coronary Anomalies Program at Texas Children’s Hospital. Relevant family history included the presence of CHD, sudden cardiac arrest/death, arrhythmia/pacemaker use, cardiomyopathy, and atherosclerotic coronary artery disease before the age of 50 years. The presence of one or more of these in 1st- or 2nd-degree relatives was considered significant.
Of 168 unrelated probands (171 patients total) included, 36 (21%) had significant family history involving 19 (53%) 1st-degree and 17 (47%) 2nd-degree relatives. Positive family history led to cardiology referral in nine (5%) patients and the presence of abnormal tests/symptoms in the remaining patients. Coronary anomalies in probands with positive family history were anomalous right (27), anomalous left (five), single right coronary artery (two), myocardial bridge (one), and anomalous circumflex coronary artery (one). Conditions present in their family members included sudden cardiac arrest/death (15, 42%), atherosclerotic coronary artery disease (14, 39%), cardiomyopathy (12, 33%), CHD (11, 31%), coronary anomalies (3, 8%), myocardial bridge (1, 3%), long-QT syndrome (2, 6%), and Wolff–Parkinson–White (1, 3%).
In patients with anomalous aortic origin of a coronary artery and/or myocardial bridges, there appears to be familial clustering of cardiac diseases in approximately 20% of patients, half of these with early occurrence of sudden cardiac arrest/death in the family.
We describe the case of a 52-day-old child who was diagnosed with a rare combination of corrected transposition of great vessels – hypoplastic right ventricle with supracardiac total anomalous pulmonary venous connection.
Researchers have been evaluating several approaches to assess acute radiation injury/toxicity markers owing to radiation exposure. Keeping in mind this background, we assumed that whole-body irradiation in single fraction in graded doses can affect the antioxidant profile in skin that could be used as an acute radiation injury/toxicity marker.
Sprague-Dawley rats were treated with CO-60 gamma radiation (dose: 1-5 Gy; dose rate: 0.85 Gy/minute). Skin samples were collected (before and after radiation up to 72 hours) and analyzed for glutathione (GSH), glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase (CAT), and lipid peroxidation (LPx).
Intra-group comparison showed significant differences in GSH, GPx, SOD, and CAT, and they declined in a dose-dependent manner from 1 to 5 Gy (P value<0.01, r value: 0.3-0.5). LPx value increased (P value<0.01, r value: 0.3-0.5) as the dose increased, except in 1 Gy (P value>0.05).
This study suggests that skin antioxidants were sensitive toward radiation even at a low radiation dose, which can be used as a predictor of radiation injury and altered in a dose-dependent manner. These biochemical parameters may have wider application in the evaluation of radiation-induced skin injury and dose assessment. (Disaster Med Public Health Preparedness. 2019;13:197–202).
Prior research has documented shared heritable contributions to non-suicidal self-injury (NSSI) and suicidal ideation (SI) as well as NSSI and suicide attempt (SA). In addition, trauma exposure has been implicated in risk for NSSI and suicide. Genetically informative studies are needed to determine common sources of liability to all three self-injurious thoughts and behaviors, and to clarify the nature of their associations with traumatic experiences.
Multivariate biometric modeling was conducted using data from 9526 twins [59% female, mean age = 31.7 years (range 24–42)] from two cohorts of the Australian Twin Registry, some of whom also participated in the Childhood Trauma Study and the Nicotine Addiction Genetics Project.
The prevalences of high-risk trauma exposure (HRT), NSSI, SI, and SA were 24.4, 5.6, 27.1, and 4.6%, respectively. All phenotypes were moderately to highly correlated. Genetic influences on self-injurious thoughts and behaviors and HRT were significant and highly correlated among men [rG = 0.59, 95% confidence interval (CI) (0.37–0.81)] and women [rG = 0.56 (0.49–0.63)]. Unique environmental influences were modestly correlated in women [rE = 0.23 (0.01–0.45)], suggesting that high-risk trauma may confer some direct risk for self-injurious thoughts and behaviors among females.
Individuals engaging in NSSI are at increased risk for suicide, and common heritable factors contribute to these associations. Preventing trauma exposure may help to mitigate risk for self-harm and suicide, either directly or indirectly via reductions in liability to psychopathology more broadly. In addition, targeting pre-existing vulnerability factors could significantly reduce risk for life-threatening behaviors among those who have experienced trauma.