How to do it: the neurological consultation with an autistic patient

Autism is a neurodevelopmental condition with a very heterogeneous presentation. Autistic people are more likely to have unmet healthcare needs, making it essential that healthcare professionals are ‘autism-aware’. In this article, we provide an overview of how autism presents and use case studies to illustrate how a neurological consultation in an outpatient clinic environment could prove challenging for a autistic person. We suggest how to improve communication with autistic patients in clinic and highlight the importance of a patient-centred and flexible approach

Bedmap2: improved ice bed, surface and thickness datasets for Antarctica

We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60° S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved data-coverage has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6% greater, the mean depth of the bed beneath the grounded ice sheet is 72 m lower and the area of ice sheet grounded on bed below sea level is increased by 10%. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets

Bedmap2: improved ice bed, surface and thickness datasets for Antarctica

We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60° S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved data-coverage has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6% greater, the mean depth of the bed beneath the grounded ice sheet is 72 m lower and the area of ice sheet grounded on bed below sea level is increased by 10%. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

On predicting the response of acoustically-excited doubly curved sandwich panels

This paper presents a recent programme of research, which has concentrated on the measurement and prediction of the dynamic response of doubly curved composite honeycomb sandwich panels to high intensity, random acoustic excitation. Four panels with varying radii of curvature were tested in a progressive wave tube (PWT) facility at overall sound pressure levels up to 164 dB (re 2×10?5 Pa). Several methods are presented to predict the dynamic response of the panels to random acoustic excitation. The first of these was the single-degree-of freedom (SDOF) approximation method, where different assumptions with regard to the spatial characteristics of the pressure loading are made. Finite element analysis (FEA) was also used to predict the response, where the pressure loading was assumed to consist of a series of travelling waves at grazing incidence to the structure. The results presented for both the SDOF approximation method and the FEA method show good agreement between predicted and measured strain values, which are also presented

Dynamic response of doubly curved honeycomb sandwich panels to random acoustic excitation. Part 2:Theoretical study

In this paper a single-degree-of-freedom model is developed to predict the dynamic response of an acoustically excited doubly curved sandwich panel. Three variants of the model are investigated, based on differing assumptions regarding the spatial distribution of the applied loading. When the loading is assumed to be uniform then the model reduces to the Miles approach, and when the loading is assumed to conform to the structural mode shape then the method is very similar to the Blevins approach. The third variant involves a more detailed consideration of the travelling wave characteristics of the applied loading, and this is found to give much improved agreement with experimental results obtained in a progressive wave tube facility. In addition, an approach using the finite element method is presented in which the response to grazing incidence excitation is computed, and this is also found to yield good agreement with the experimental results

Understanding stigma in autism: a narrative review and theoretical model

The experience of stigma by autistic people is relatively understudied, despite contributing to a range of poor outcomes and having an overarching impact on well-being. The current review of the literature synthesizes research to determine what is currently known and presents a theoretical model of autism stigma. Autism stigma is primarily influenced by a public and professional understanding of autism in combination with interpretation of visible autistic traits. Moderating factors include the quality and quantity of contact with autistic people, cultural factors, sex and gender, individual differences, and diagnostic disclosure. Stigma can reduce well-being as well as increase the presence of camouflaging behaviors, which mask autistic traits. Caregivers of autistic people can experience stigma by association, that is, affiliate stigma, which can impact their own well-being. A variety of interventions and approaches to reduce stigma are discussed, including “autism friendly” spaces, positive media representation, educational and psychosocial training for the public and professionals, as well as cultural and systemic shifts that foster inclusivity and recognize neurodiversity