Sensory motor systems of artificial and natural hands

The surgeon Ambroise Paré designed an anthropomorphic hand for wounded soldiers in the 16th century. Since that time, there have been advances in technology through the use of computer-aided design, modern materials, electronic controllers and sensors to realise artificial hands which have good functionality and reliability. Data from touch, object slip, finger position and temperature sensors, mounted in the fingers and on the palm, can be used in feedback loops to automatically hold objects. A study of the natural neuromuscular systems reveals a complexity which can only in part be realised today with technology. Highlights of the parallels and differences between natural and artificial hands are discussed with reference to the Southampton Hand. The anatomical structure of parts of the natural systems can be made artificially such as the antagonist muscles using tendons. Theses solutions look promising as they are based on the natural form but in practice lack the desired physical specification. However, concepts of the lower spinal loops can be mimicked in principle. Some future devices will require greater skills from the surgeon to create the interface between the natural system and an artificial device. Such developments may offer a more natural control with ease of use for the limb deficient person

Longitudinal evaluation of cognitive functioning in young children with type 1 diabetes over 18 months

OBJECTIVE: Decrements in cognitive function may already be evident in young children with type 1 diabetes (T1D). Here we report prospectively acquired cognitive results over 18 months in a large cohort of young children with and without T1D. METHODS: 144 children with T1D (mean HbA1c: 7.9%) and 70 age-matched healthy controls (mean age both groups 8.5 years; median diabetes duration 3.9 yrs; mean age of onset 4.1 yrs) underwent neuropsychological testing at baseline and after 18-months of follow-up. We hypothesized that group differences observed at baseline would be more pronounced after 18 months, particularly in those T1D patients with greatest exposure to glycemic extremes. RESULTS: Cognitive domain scores did not differ between groups at the 18 month testing session and did not change differently between groups over the follow-up period. However, within the T1D group, a history of diabetic ketoacidosis (DKA) was correlated with lower Verbal IQ and greater hyperglycemia exposure (HbA1c area under the curve) was inversely correlated to executive functions test performance. In addition, those with a history of both types of exposure performed most poorly on measures of executive function. CONCLUSIONS: The subtle cognitive differences between T1D children and nondiabetic controls observed at baseline were not observed 18 months later. Within the T1D group, as at baseline, relationships between cognition (VIQ and executive functions) and glycemic variables (chronic hyperglycemia and DKA history) were evident. Continued longitudinal study of this T1D cohort and their carefully matched healthy comparison group is planned

Anxiety and Interpretation of Ambiguity in Autistic Children, Typical Children and Their Mothers

Anxiety is highly prevalent in autistic children. Yet interpretation biases implicated in anxiety in non-autistic individuals have received little research attention in this group. Twenty-two autistic children and 25 typical children completed an ambiguous scenarios interview and questionnaire-based measures of anxiety. A subsample of mothers completed parent-report and adult relevant versions of the interview and anxiety questionnaires. Autistic children self-reported similar interpretations of ambiguous scenarios, and similar levels of anxiety, to their typical peers. In contrast, mothers of autistic children reported greater levels of anxiety, and more negative interpretations of ambiguous scenarios in both their children and themselves, relative to mothers of typical children. These data highlight the importance of including autistic children's self-reports when measuring and treating anxiety

Relationship between abuse and neglect in childhood and diabetes in adulthood: Differential effects by sex, national longitudinal study of adolescent health

INTRODUCTION: Few studies have investigated links between child abuse and neglect and diabetes mellitus in nationally representative samples, and none have explored the role of obesity in the relationship. We sought to determine whether child abuse and neglect were associated with diabetes and if so, whether obesity mediated this relationship in a population-representative sample of young adults. METHODS: We used data from 14,493 participants aged 24 to 34 years from Wave IV of the National Longitudinal Study of Adolescent Health to study associations between self-reported child abuse (sexual, physical, or emotional abuse) and neglect as children and diabetes or prediabetes in young adulthood. We conducted sex-stratified logistic regression analyses to evaluate associations in models before and after the addition of body mass index (BMI) as a covariate. RESULTS: Although the prevalence of diabetes was similar for men and women (7.0% vs 6.7%), men were more likely than women to have prediabetes (36.3% vs 24.6%; omnibus P < .001). Among men, recurrent sexual abuse (≥3 lifetime incidents) was significantly associated with diabetes (OR, 3.66; 95% CI, 1.31–10.24), but not with prediabetes. There was no evidence of mediation by BMI. No forms of child abuse or neglect were associated with diabetes or prediabetes among women. CONCLUSIONS: Recurrent sexual abuse is robustly associated with diabetes in young adult men, independently of other forms of child abuse or neglect and BMI. Future research should explore other potential mechanisms for this association to identify avenues for prevention of diabetes among men who have experienced sexual abuse

Infections in the first year of life and development of beta cell autoimmunity and clinical type 1 diabetes in high-risk individuals : the TRIGR cohort

Aims/hypothesis Accumulated data suggest that infections in early life contribute to the development of type 1 diabetes. Using data from the Trial to Reduce IDDM in the Genetically at Risk (TRIGR), we set out to assess whether children who later developed diabetes-related autoantibodies and/or clinical type 1 diabetes had different exposure to infections early in life compared with those who did not. Methods A cohort of 2159 children with an affected first-degree relative and HLA-conferred susceptibility to type 1 diabetes were recruited between 2002 and 2007 and followed until 2017. Infections were registered prospectively. The relationship between infections in the first year of life and the development of autoantibodies or clinical type 1 diabetes was analysed using univariable and multivariable Cox regression models. As this study was exploratory, no adjustment was made for multiple comparisons. Results Adjusting for HLA, sex, breastfeeding duration and birth order, those who had seven or more infections during their first year of life were more likely to develop at least one positive type 1 diabetes-related autoantibody (p=0.028, HR 9.166 [95% CI 1.277, 65.81]) compared with those who had no infections. Those who had their first viral infection aged between 6 and 12 months were less likely to develop at least one positive type 1 diabetes-related antibody (p=0.043, HR 0.828 [95% CI 0.690, 0.994]) or multiple antibodies (p=0.0351, HR 0.664 [95% CI 0.453, 0.972]). Those who had ever had an unspecified bacterial infection were more likely to develop at least one positive type 1 diabetes-related autoantibody (p=0.013, HR 1.412 [95% CI 1.075, 1.854]), to develop multiple antibodies (p=0.037, HR 1.652 [95% CI 1.030, 2.649]) and to develop clinical type 1 diabetes (p=0.011, HR 2.066 [95% CI 1.182, 3.613]). Conclusions/interpretation We found weak support for the assumption that viral infections early in life may initiate the autoimmune process or later development of type 1 diabetes. In contrast, certain bacterial infections appeared to increase the risk of both multiple autoantibodies and clinical type 1 diabetes.Peer reviewe

Genomics reveals historic and contemporary transmission dynamics of a bacterial disease among wildlife and livestock

Whole-genome sequencing has provided fundamental insights into infectious disease epidemiology, but has rarely been used for examining transmission dynamics of a bacterial pathogen in wildlife. In the Greater Yellowstone Ecosystem (GYE), outbreaks of brucellosis have increased in cattle along with rising seroprevalence in elk. Here we use a genomic approach to examine Brucella abortus evolution, cross-species transmission and spatial spread in the GYE. We find that brucellosis was introduced into wildlife in this region at least five times. The diffusion rate varies among Brucella lineages (∼3 to 8 km per year) and over time. We also estimate 12 host transitions from bison to elk, and 5 from elk to bison. Our results support the notion that free-ranging elk are currently a self-sustaining brucellosis reservoir and the source of livestock infections, and that control measures in bison are unlikely to affect the dynamics of unrelated strains circulating in nearby elk populations

Utility of using electrocardiogram measures of heart rate variability as a measure of cardiovascular autonomic neuropathy in type 1 diabetes patients

AIMS/INTRODUCTION: Cardiovascular autonomic neuropathy (CAN) is a predictor of cardiovascular disease and mortality. Cardiovascular reflex tests (CARTs) are the gold standard for the diagnosis of CAN, but might not be feasible in large research cohorts or in clinical care. We investigated whether measures of heart rate variability obtained from standard electrocardiogram (ECG) recordings provide a reliable measure of CAN. MATERIALS AND METHODS: Standardized CARTs (R-R response to paced breathing, Valsalva, postural changes) and digitized 12-lead resting ECGs were obtained concomitantly in Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications participants (n = 311). Standard deviation of normally conducted R-R intervals (SDNN) and the root mean square of successive differences between normal-to-normal R-R intervals (rMSSD) were measured from ECG. Sensitivity, specificity, probability of correct classification and Kappa statistics evaluated the agreement between ECG-derived CAN and CARTs-defined CAN. RESULTS: Participants with CARTs-defined CAN had significantly lower SDNN and rMSSD compared with those without CAN (P \u3c 0.001). The optimal cut-off points of ECG-derived CAN were \u3c17.13 and \u3c24.94 ms for SDNN and rMSSD, respectively. SDNN plays a dominant role in defining CAN, with an area under the curve of 0.73, indicating fair test performance. The Kappa statistic for SDNN was 0.41 (95% confidence interval 0.30-0.51) for the optimal cut-off point, showing fair agreement with CARTs-defined CAN. Combining SDNN and rMSSD optimal cut-off points does not provide additional predictive power for CAN. CONCLUSIONS: These analyses are the first to show the agreement between indices of heart rate variability derived from ECGs and the gold standard CARTs, thus supporting potential use as a measure of CAN in clinical research and clinical care