No-biopsy strategy for coeliac disease is applicable in adult patients: a 'real-world' Scottish experience.

Objective: Emergency interim guidance from the British Society for Gastroenterology (BSG) states that a no-biopsy strategy is possible to diagnose coeliac disease (CD) in adults with elevated transglutaminase IgA antibody (TGA-IgA) levels. We aimed to determine if the suggested TGA-IgA ≥10× ULN is safe and robust in making the diagnosis in adult patients in Scotland. We also aimed to establish if any important co-diagnoses would be missed if no biopsy was performed. Method: All positive coeliac serology results for patients aged >15 years in Scotland in 2016 (Grampian 2019) were accessed. Data were collected on demographics, TGA-IgA titres, D1 sampling, histology and macroscopic findings at upper and lower gastrointestinal (GI) endoscopy. Results: 1037/1429 patients with positive serology proceeded to biopsy, of which 796/1037 (76.8%) were diagnosed as CD. A total of 320/322 (99.37%) patients with TGA-IgA ≥10× ULN were diagnosed as CD giving the cut-off a positive predictive value of 99.38%. No significant co-pathology was found at endoscopy in these patients. Conclusion: Our results show that a no-biopsy strategy using a cut-off of TGA-IgA ≥10× ULN is safe to diagnose CD and that no important pathology would be missed. The European Society for Paediatric Gastroenterology, Hepatology and Nutrition 2020 and BSG COVID-19 interim guidelines are applicable to adult patients in Scotland.

Supporting Parents' Services Access During the COVID-19 Pandemic Through the Infant-Toddler Court Team Program.

INTRODUCTION: Infant-Toddler Court Teams (ITCTs) are a collaborative practice designed to improve timely identification and receipt of needed services for families of infants and toddlers involved in the child welfare system and their families. The goal of the study was to explore the impact of the first year of COVID compared to the previous year, in the context of ITCT support, on: (1) parents' access to services; (2) parents' services receipt and access within 30 days and within 14 days from referral; and (3) predictors of services access and receipt. METHODS: Overall, 897 instances of services needs were analyzed, 411 pre-COVID and 486 during COVID. Logistic regression models were used to test for differences pre- and during COVID, controlling for covariates. RESULTS: A reduction in service access was found across all services during COVID (OR = 0.2, CI: 0.1-0.3, p < .0001). Nevertheless, if a service was still available, parents were able to maintain similar levels of receipt within 30 days and within 14 days as before COVID. Moreover, a higher percentage of parents in need received mental health services in 30 or fewer days and substance use disorder services in both 14 and 30 or fewer days during COVID compared to pre-COVID. DISCUSSION: This success is notable given the significant disruption to the availability of services and barriers to accessing services caused by the pandemic. ITCTs provided a robust platform for supporting the health and well-being of families with very young children in the face of a severely reduced service landscape due to COVID-19.

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g. cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Effect of physical activity during COVID-19 on the sleep health of community-level athletes in Australia.

The COVID-19 outbreak presents a serious health challenges, with Australia enforcing tight restrictions, impacting sporting activities and sleep health of many Australians. Routine lifestyle patterns (physical activity and employment) are important to maintaining overall sleep health. Current literature indicates COVID-19 pandemic negatively affected the employment status and sport engagement. The aim of this study was to explore the effect of physical activity during COVID-19 on sleep health, and its association with employment and sport engagement of community-level athletes throughout Australia. Participants self-reported sleep health prior to COVID-19 (pre-sleep) and over the month prior to data collection (during-sleep) using the validated 5-item Satisfaction Alertness Timing Efficiency and Duration questionnaire (SATED). Wilcoxon Signed Rank Test assessed the difference in pre- and during perceived sleep health scores. A generalized linear model was used to assess the impact of sporting and demographic factors on a community athlete's change in perceived sleep health score. A total of 139 community-level Australian athletes responded. The majority of participants were aged 18-30 and engaged in full-time employment prior to COVID-19 (n = 82, 54%). Eight percent of participants were unemployed prior to the COVID-19 pandemic (n = 12, 8%). Our findings show that sleep health values were higher during COVID-19, with 91.4% of respondents able to maintain some form of physical activity during the pandemic. Together, our results show better sleep health scores reported by the respondents who maintained or lost employment and maintained sporting engagements during the pandemic.

Epigenetic scores for the circulating proteome as tools for disease prediction.

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample (Generation Scotland; n = 9537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore-disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors, and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.

Although our genetic code does not change throughout our lives, our genes can be turned on and off as a result of epigenetics. Epigenetics can track how the environment and even certain behaviors add or remove small chemical markers to the DNA that makes up the genome. The type and location of these markers may affect whether genes are active or silent, this is, whether the protein coded for by that gene is being produced or not. One common epigenetic marker is known as DNA methylation. DNA methylation has been linked to the levels of a range of proteins in our cells and the risk people have of developing chronic diseases. Blood samples can be used to determine the epigenetic markers a person has on their genome and to study the abundance of many proteins. Gadd, Hillary, McCartney, Zaghlool et al. studied the relationships between DNA methylation and the abundance of 953 different proteins in blood samples from individuals in the German KORA cohort and the Scottish Lothian Birth Cohort 1936. They then used machine learning to analyze the relationship between epigenetic markers found in people's blood and the abundance of proteins, obtaining epigenetic scores or 'EpiScores' for each protein. They found 109 proteins for which DNA methylation patterns explained between at least 1% and up to 58% of the variation in protein levels. Integrating the 'EpiScores' with 14 years of medical records for more than 9000 individuals from the Generation Scotland study revealed 137 connections between EpiScores for proteins and a future diagnosis of common adverse health outcomes. These included diabetes, stroke, depression, Alzheimer's dementia, various cancers, and inflammatory conditions such as rheumatoid arthritis and inflammatory bowel disease. Age-related chronic diseases are a growing issue worldwide and place pressure on healthcare systems. They also severely reduce quality of life for individuals over many years. This work shows how epigenetic scores based on protein levels in the blood could predict a person's risk of several of these diseases. In the case of type 2 diabetes, the EpiScore results replicated previous research linking protein levels in the blood to future diagnosis of diabetes. Protein EpiScores could therefore allow researchers to identify people with the highest risk of disease, making it possible to intervene early and prevent these people from developing chronic conditions as they age.

Modelling the active SARS-CoV-2 helicase complex as a basis for structure-based inhibitor design.

The RNA helicase (non-structural protein 13, NSP13) of SARS-CoV-2 is essential for viral replication, and it is highly conserved among the coronaviridae family, thus a prominent drug target to treat COVID-19. We present here structural models and dynamics of the helicase in complex with its native substrates based on thorough analysis of homologous sequences and existing experimental structures. We performed and analysed microseconds of molecular dynamics (MD) simulations, and our model provides valuable insights to the binding of the ATP and ssRNA at the atomic level. We identify the principal motions characterising the enzyme and highlight the effect of the natural substrates on this dynamics. Furthermore, allosteric binding sites are suggested by our pocket analysis. Our obtained structural and dynamical insights are important for subsequent studies of the catalytic function and for the development of specific inhibitors at our characterised binding pockets for this promising COVID-19 drug target.

A Survey to Evaluate the Association of COVID-19 Restrictions on Perceived Mood and Coping in Australian Community Level Athletes.

Highlights: No differences in coping or well-being in Australian community athletes based on the level of support received during COVID-19 restrictions.Community level athletes had better coping when a training program was provided.No difference between individual or team community athletes for well-being or coping scores. Australian community level athletes faced unprecedented changes to their training and competition options as the global COVID-19 pandemic took a stronghold. This disruption was predicted to have a negative impact on emotional well-being as communities braced through periods of social isolation and physical distancing requirements. This study provides an Australian perspective on the emotional well-being of community level athletes and the extent to which they coped during the COVID-19 pandemic. Emotional well-being and coping were measured using the Brief Emotional Experience Scale and the 28-item Brief Cope Scale. Both instruments were administered along with other questions pertaining to participant demographics and training status via an online survey between April and June 2020. The survey was disseminated to community athletes through word-of-mouth and social media platforms. No significant differences in emotional well-being were observed between athlete groups as a result of COVID-19 and its associated restrictions. Coping scores also appeared to be preserved in Australian community athletes, which contrasts the impact expected as a result of the COVID-19 pandemic. While tentative, the observed preservation in coping may have buffered potential declines in emotional well-being, which has been documented in professional and semi-professional athletes and the general population. These unexpected findings and tentative suppositions warrant further investigation and highlight the importance of conducting a country- or region-specific approach to examining the impact of COVID-19 on community athletes, as responses to COVID-19 are undoubtedly not consistent throughout the world.