Diffusion tensor magnetic resonance imaging (MRI) is a possible new means of elucidating the anatomic structure of the myocardium. It enjoys several advantages over traditional histological approaches, including the ability to rapidly measure fiber organization in isolated, perfused, arrested hearts, thereby avoiding fixation and sectioning of artifacts. However, quantitative validation of this MRI method has been lacking. Here, fiber orientations estimated in the same locations in the same heart using both diffusion tensor MRI and histology are compared in a total of two perfused rabbit hearts. Fiber orientations were statistically similar for both methods and differed on average by 12° at any single location. This is similar to the 10° uncertainty in fiber orientation achieved with histology. In addition, imaging studies performed in a total of seven hearts support a level of organization beyond the myofiber, the recently described laminar organization of the ventricular myocardium.

Background:Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a "stay at home" order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. : medRxiv preprint second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Discussion:Our work supports the decision to apply stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. We provide strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units. 2 to a cluster of pneumonia cases [1]. The virus was identified as a novel strain of coronavirus on 7th 3 January 2020 [2] and the first known death as a result of the disease occurred two days later [1]. Over 4 the next few days, cases were reported in several other cities in China and in other countries around 5 the world including South Korea, Japan and the United States of America. On 23rd January, the 6Chinese government issued an order for Wuhan city to enter "lockdown", whereby all public transport 7 was suspended and residents were not allowed to leave the city. Over the next 24 hours, these measures 8 were extended to all the major cities in Hubei province in an attempt to prevent further spread of 9 disease.

The COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the basic reproductive ratio, $R$, has taken on special significance in terms of the general understanding of whether the epidemic is under control ($R<1$). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks. Here, we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence.

BackgroundTo examine the effectiveness and acceptability of an 8-week individual tailored cognitive behavioural therapy (CBT) intervention for the treatment of depressive symptoms in those newly diagnosed with multiple sclerosis.MethodsThe current study presents a pilot, parallel group randomized controlled trial (RCT) with an allocation ratio of 1:1 conducted in a large research and teaching hospital in Melbourne, Australia. 30 individuals with a mean age of 36.93 years (SD = 9.63) who were newly diagnosed with multiple sclerosis (MS) (X = 24.87 months, SD = 15.61) were randomized to the CBT intervention (n = 15) or treatment as usual (TAU) (n = 15). The primary outcome was level of depressive symptoms using the Beck Depression Inventory-II (BDI-II). Secondary outcomes were level of anxiety, fatigue and pain impact, sleep quality, coping, acceptance of MS illness, MS related quality of life, social support, and resilience. Tertiary outcomes were acceptability and adherence to the intervention.ResultsLarge between group treatment effects were found for level of depressive symptoms at post and at 20 weeks follow-up (d = 1.66–1.34). There were also small to large group treatment effects for level of anxiety, fatigue and pain impact, sleep quality, MS related quality of life, resilience, and social support at post and at 20 weeks follow-up (d = 0.17–1.63). There were no drop-outs and participants completed all treatment modules. All participants reported the treatment as ‘very useful’, and most (73.4%) reported that the intervention had addressed their problems ‘completely’.ConclusionsThese data suggest that the tailored early intervention is appropriate and clinically effective for the treatment of depressive symptoms in those newly diagnosed with MS. A larger RCT comparing the CBT intervention with an active comparative treatment with longer term follow-up and cost effectiveness analyses is warranted. The pilot trial has been retrospectively registered on 28/04/2016 with the ISRCTN registry (trial ID ISRCTN10423371).

Background: In the UK, cases of COVID-19 have been declining since mid-April and there is good evidence to suggest that the effective reproduction number has dropped below 1, leading to a multi-phase relaxation plan for the country to emerge from lockdown. As part of this staggered process, primary schools are scheduled to partially reopen on 1st June. Evidence from a range of sources suggests that children are, in general, only mildly affected by the disease and have low mortality rates, though there is less certainty regarding children's role in transmission. Therefore, there is wide discussion on the impact of reopening schools. Methods: We compare eight strategies for reopening primary and secondary schools in England from 1st June, focusing on the return of particular year groups and the associated epidemic consequences. This is assessed through model simulation, modifying a previously developed dynamic transmission model for SARS-CoV-2. We quantify how the process of reopening schools affected contact patterns and anticipated secondary infections, the relative change in R according to the extent of school reopening, and determine the public health impact via estimated change in clinical cases and its sensitivity to decreases in adherence post strict lockdown. Findings: Whilst reopening schools, in any form, results in more mixing between children, an increase in R and hence transmission of the disease, the magnitude of that increase can be low dependent upon the age-groups that return to school and the behaviour of the remaining population. We predict that reopening schools in a way that allows half class sizes or that is focused on younger children is unlikely to push R above one, although there is noticeable variation between the regions of the country. Given that older children have a greater number of social contacts and hence a greater potential for transmission, our findings suggest reopening secondary schools results in larger increases in case burden than only reopening primary schools; reopening both generates the largest increase and could push R above one in some regions. The impact of less social-distancing in the rest of the population, generally has far larger effects than reopening schools and exacerbates the impacts of reopening. Discussion: Our work indicates that any reopening of schools will result in increased mixing and infection amongst children and the wider population, although the opening of schools alone is unlikely to push the value of R above one. However, impacts of other recent relaxations of lockdown measures are yet to be quantified, suggesting some regions may be closer to the critical threshold that would lead to a growth in cases. Given the uncertainties, in part due to limited data on COVID-19 in children, school reopening should be carefully monitored. Ultimately, the decision about reopening classrooms is a difficult trade-off between increased epidemiological consequences and the emotional, educational and developmental needs of children.