Detection of gait events using a gyroscope sensor in FES drop-foot correction

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Self-perceived disease activity was the strongest predictor of COVID-19 pandemic-related concerns in young people with autoimmune rheumatic diseases, irrespective of their gender, with females reporting higher concerns

OBJECTIVE: We report the results of a pilot young patient survey that targeted patients with JSLE and JDM, exploring well-being, resilience and general concern about the coronavirus disease 2019 (COVID-19) pandemic as well as self-assessment of disease activity. METHODS: The survey was completed anonymously by patients who had been approached via the automatically generated hospital database between June and December 2020. In addition to disease characteristics, geographic location, education and employment level, we explored young patients’ resilience, mood and feelings, mental well-being, self-assessed disease activity and general COVID-19 concerns using validated tools and visual analogue scales. RESULTS: This pilot study found that self-perceived disease activity was the strongest predictor of COVID-19 concern, irrespective of gender, employment and education status or well-being and resilience. Generalized concerns regarding the COVID-19 pandemic were significantly higher in females, although their self-reported DASs were comparable to male respondents. CONCLUSION: Our findings highlight a gender bias in the generalized concern related to the COVID-19 pandemic, irrespective of the examined potential confounders. This suggests the need for further research around young patient self-reported outcomes outside hospital visits, especially in the context of gender differences and potential challenges of future pandemics

Marital status and gender differences as key determinants of COVID-19 impact on well-being, job satisfaction and resilience in health care workers and staff working in academia in the UK during the first wave of the pandemic

BACKGROUND: The COVID-19 pandemic is an unprecedented global public health crisis that continues to exert immense pressure on healthcare and related professional staff and services. The impact on staff wellbeing is likely to be influenced by a combination of modifiable and non-modifiable factors. OBJECTIVES: The aim of this study is to evaluate the effect of the COVID-19 pandemic on the self-reported wellbeing, resilience, and job satisfaction of National Health Service (NHS) and university staff working in the field of healthcare and medical research. METHODS: We conducted a cross sectional survey of NHS and UK university staff throughout the COVID-19 pandemic between May-November 2020. The anonymous and voluntary survey was disseminated through social media platforms, and via e-mail to members of professional and medical bodies. The data was analysed using descriptive and regression (R) statistics. RESULTS: The enjoyment of work and satisfaction outside of work was significantly negatively impacted by the COVID-19 pandemic for all of staff groups independent of other variables. Furthermore, married women reporting significantly lower well-being than married men (P=0.028). Additionally, the well-being of single females was significantly lower than both married women and men (P=0.017 and P<0.0001, respectively). Gender differences were also found in satisfaction outside of work, with women reporting higher satisfaction than men before the COVID-19 pandemic (P=0.0002). CONCLUSION: Our study confirms that the enjoyment of work and general satisfaction of staff members has been significantly affected by the first wave of the COVID-19 pandemic. Interestingly, being married appears to be a protective factor for wellbeing and resilience but the effect may be reversed for life satisfaction outside work. Our survey highlights the critical need for further research to examine gender differences using a wider range of methods

Are power calculations useful? A multicentre neuroimaging study

There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources

Cognition in males and females with autism: similarities and differences

The male bias in autism spectrum conditions (ASC) has led to females with ASC being under-researched. This lack of attention to females could hide variability due to sex that may explain some of the heterogeneity within ASC. In this study we investigate four key cognitive domains (mentalizing and emotion perception, executive function, perceptual attention to detail, and motor function) in ASC, to test for similarities and differences between males and females with and without ASC (n = 128 adults; n = 32 per group). In the mentalizing and facial emotion perception domain, males and females with ASC showed similar deficits compared to neurotypical controls. However, in attention to detail and dexterity involving executive function, although males with ASC showed poorer performance relative to neurotypical males, females with ASC performed comparably to neurotypical females. We conclude that performance in the social-cognitive domain is equally impaired in male and female adults with ASC. However, in specific non-social cognitive domains, performance within ASC depends on sex. This suggests that in specific domains, cognitive profiles in ASC are modulated by sex

Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women

Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently

Frontal networks in adults with autism spectrum disorder.

It has been postulated that autism spectrum disorder is underpinned by an 'atypical connectivity' involving higher-order association brain regions. To test this hypothesis in a large cohort of adults with autism spectrum disorder we compared the white matter networks of 61 adult males with autism spectrum disorder and 61 neurotypical controls, using two complementary approaches to diffusion tensor magnetic resonance imaging. First, we applied tract-based spatial statistics, a 'whole brain' non-hypothesis driven method, to identify differences in white matter networks in adults with autism spectrum disorder. Following this we used a tract-specific analysis, based on tractography, to carry out a more detailed analysis of individual tracts identified by tract-based spatial statistics. Finally, within the autism spectrum disorder group, we studied the relationship between diffusion measures and autistic symptom severity. Tract-based spatial statistics revealed that autism spectrum disorder was associated with significantly reduced fractional anisotropy in regions that included frontal lobe pathways. Tractography analysis of these specific pathways showed increased mean and perpendicular diffusivity, and reduced number of streamlines in the anterior and long segments of the arcuate fasciculus, cingulum and uncinate--predominantly in the left hemisphere. Abnormalities were also evident in the anterior portions of the corpus callosum connecting left and right frontal lobes. The degree of microstructural alteration of the arcuate and uncinate fasciculi was associated with severity of symptoms in language and social reciprocity in childhood. Our results indicated that autism spectrum disorder is a developmental condition associated with abnormal connectivity of the frontal lobes. Furthermore our findings showed that male adults with autism spectrum disorder have regional differences in brain anatomy, which correlate with specific aspects of autistic symptoms. Overall these results suggest that autism spectrum disorder is a condition linked to aberrant developmental trajectories of the frontal networks that persist in adult life

Unsupervised data-driven stratification of mentalizing heterogeneity in autism.

Individuals affected by autism spectrum conditions (ASC) are considerably heterogeneous. Novel approaches are needed to parse this heterogeneity to enhance precision in clinical and translational research. Applying a clustering approach taken from genomics and systems biology on two large independent cognitive datasets of adults with and without ASC (n = 694; n = 249), we find replicable evidence for 5 discrete ASC subgroups that are highly differentiated in item-level performance on an explicit mentalizing task tapping ability to read complex emotion and mental states from the eye region of the face (Reading the Mind in the Eyes Test; RMET). Three subgroups comprising 45-62% of ASC adults show evidence for large impairments (Cohen's d = -1.03 to -11.21), while other subgroups are effectively unimpaired. These findings delineate robust natural subdivisions within the ASC population that may allow for more individualized inferences and accelerate research towards precision medicine goals.This study was supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) East of England at Cambridgeshire and Peterborough NHS Foundation Trust. This study was also conducted in association with the European Autism Interventions—A Multicentre Study for Developing New Medications (EU-AIMS) consortium; EU-AIMS receives support from the Innovative Medicines Initiative Joint Undertaking under grant agreement number 115300, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013), EFPIA companies, and Autism Speaks. This study was also supported by grants from the UK Medical Research Council (MRC) (G0600977), the Wellcome Trust (091774/Z/10/Z), and the Autism Research Trust (ART). M-CL and AR received support from the William Binks Autism Neuroscience Fellowship at the University of Cambridge. M-CL received support from the O’Brien Scholars Program within the Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health and The Hospital for Sick Children, Toronto.This is the final version of the article. It first appeared from Nature Publishing Group via https://doi.org/10.1038/srep3533

ORIGINAL ARTICLE - Near infrared spectroscopy reveals neural activation during face perception in infants and adults

We used near infrared spectroscopy to measure changes in cerebral oxygenation in both human infants and adults as they viewed images of faces or control “visual noise” stimuli. At an occipital site, adults showed a significant increase in oxyhaemoglobin and a contrasting pattern of results was observed in infants. While the same general difference between the processing of the two stimuli was observed, a larger decrease in oxyhemoglobin concentration in response to faces than to visual noise was found in infants. These results demonstrate that near infrared spectroscopy can detect differences in stimulus processing induced by a complex visual stimulus in both infants and adults. (J Pediatr Neurol 2004; 2(2): 85-89)