SARS-CoV-2 induces acute neurological signs while Calcitonin Gene-Related Peptide (CGRP) signaling blockade reduces interleukin 6 (IL-6) release and weight loss in mouse models (preprint)

COVID-19 can result in neurological symptoms such as fever, headache, dizziness, and nausea. We evaluated whether the Calcitonin Gene-Related Peptide (CGRP) receptor antagonist, olcegepant, used in migraine treatment could mitigate acute neuroinflammatory and neurological responses to SARS-COV-2 infection. We infected wildtype C57BL/6J and 129/SvEv mice, and a 129 CGRP-null mouse line with a mouse-adapted SARS-CoV-2 virus, and evaluated the effect of CGRP receptor antagonism on the outcome of that infection. We determined that CGRP receptor antagonism provided protection from permanent weight loss in older (>12 m) C57BL/6J and 129 SvEv mice. We also observed acute fever and motion-induced dizziness in all older mice, regardless of treatment. However, in both wildtype mouse lines, CGRP antagonism reduced acute interleukin 6 (IL-6) levels by half, with virtually no IL-6 release in mice lacking CGRP. These findings suggest that blockage of CGRP signaling protects against acute IL-6 release and subsequent inflammatory events after SARS-CoV-2 infection.

Implementation and sustainability of public health approaches for mental health and wellbeing in schools

Aims: With increasing prevalence of emotional difficulties in children and young people in England, there is a growing emphasis on prevention programs delivered in school settings. The Education for Wellbeing program is working with around 400 schools in England to evaluate five universal mental health and wellbeing interventions Here, we present an overview of the Education for Wellbeing program and describe patterns across different school settings in barriers and facilitators to sustaining intervention delivery Methods: This study draws on interviews with staff and pupils from eight schools over multiple timepoints, including during the COVID- 19 pandemic. Qualitative methods were used to cluster schools with similar 'journeys' over a three-year period in terms of staff members' experiences of intervention delivery and perceived barriers and facilitators to sustaining delivery Results: The analysis demonstrated patterns in schools' journeys over time, each underpinned by a range of barriers and facilitators to the sustainability of the interventions. Four clusters of schools were identified each representing one overarching pattern: 'Spreading and embedding', 'Trialled and moved on', 'Everything's changed', and 'Built into the curriculum for now' Conclusion(s): The variety in schools' experiences highlights the complexity of both school settings and the process of implementing and sustaining interventions. These findings suggest that the environment and conditions into which a public health intervention is placed may be as, if not more, important than the intervention itself, and provoke important questions regarding future research and intervention development.

Systematic Review of Qualitative and Quantitative Studies on Perceived Employability of Graduates

The assessment of future students' employability by the Institute of Higher Learning in collaboration with career centres is one of the most crucial steps in the educational industry for establishing an active and ascendable plan. Predictive analysis for this project is done using machine learning. This study investigates the Employability Signals of Undergraduates in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria. The findings demonstrate that higher education was where the most accurate predictor of undergraduate students' employability was initially examined. The study's conclusions can be used to develop a roadmap that will make it simpler to use predictive analytics. The findings of this study may also facilitate the creation and application of predictive analytics, one of the possible approaches for analysing the education data gathered during the pre-covid period for this study. Systematic literature reviews should be trustworthy, repeatable, and valid when used in scientific investigations. As a result, the inquiry will reach a conclusion based on the evaluations found on pertinent and customized dates. © 2023 IEEE.

‘Going through the Eye of the Storm’: The Impact of Covid-19 on the Long-Term Dementia Care Workforce

Context: Official guidance on Covid-19 failed to take account of the prevalence of dementia among people living in care homes or its implications for implementing infection control measures. Objective: To gain insight into the experience of those charged with implementing Covid-19 restrictions in long-term dementia care environments. Methods: Twenty members of the long-term dementia care workforce shared their experiences, using interviews, online discussion groups, or written personal accounts. Findings: Thematic analysis identified four key aspects of the participants’ experience: 1) Confusion and stress arising from the implementation of new policies, which changed very frequently;2) The negative impact of measures such as social isolation, PPE, and coronavirus testing on people living with dementia and their families;3) The impact on their own mental health and well-being over time;4) Creative problem-solving and collaboration in the face of these challenges. Analysis suggests that the social care dementia workforce faced many of the same challenges identified for acute healthcare workers, with the addition of a sense of personal bereavement and responsibility when residents died. Limitations: The study is United Kingdom (UK)-dominated. Data were collected retro-spectively and relate predominantly to the first wave of the pandemic. Most participants were studying on a MSc programme on which the first and third authors teach. Implications: Future guidance to care homes must take account of the high numbers of people with cognitive difficulties living in such environments. Co-designed strategies are needed to address the longer-term implications of Covid-19 for the social care dementia workforce. © 2022 The Author(s).

MINI: AN ENERGY-FLEXIBLE POINT-OF-CARE DEVICE FOR HIGH-THROUGHPUT SCREENING

In 2020, the COVID-19 pandemic demonstrated the need for robust, high throughput diagnostics capable of screening large populations. To overcome this limitation, we have developed MINI: a portable, high-throughput screening device for COVID-19 infection in community and limited resource settings for up to 96 samples simultaneously. MINI operates on electrical, solar, or thermal energy and is robust against power interruptions. Here, we provide a complete description of MINI, and preliminary validation of the system utilizing a predecessor device and nasopharyngeal (NP) swabs samples - results in <30 minutes post RNA extraction and purification. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

Business Angel Investing During the COVID-19 Pandemic

The onset of the coronavirus pandemic quickly raised concerns that the associated economic disruption would result in a collapse in angel investing which—given their critical role in the entrepreneurial ecosystem—would have an adverse impact on entrepreneurial activity. Given the discretionary nature of investing in new and early-stage entrepreneurial businesses, the uncertainty about the impact of COVID-19 on their financial assets (e.g. shares, property) was expected to prompt angels to pause their investment activity. Meanwhile, those angels who continued to invest were expected to focus on their existing portfolios rather than making new investments. A further source of disruption was the shift in the investment process from face-to-face to online meetings. The evidence that emerged in the early months of the pandemic indicated that there had been a significant decline in angel investing. But by the autumn of 2020, there were clear signs of a recovery in angel investing. Moreover, contrary to expectations there has not been a sustained shift by angels to making follow-on investments in their portfolio companies and away from new investments. The resilience of angel investing reflects several factors. The confidence of angels increased as the COVID vaccine roll-out programme started, driving economic recovery and as they became more familiar with the new business environment. Moreover, entrepreneurs who had deferred seeking funding in the early months of the pandemic had return to the market. Angels also had the opportunity to see more deals as investment pitching moved online. Both angels and angel groups had also become more accustomed to the digital environment for connecting with people and more comfortable in investing in people that they had never met. And attractive investment opportunities had emerged as entrepreneurs developed creative and innovate solutions to the problems arising from the disruptions created by COVID. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The effects of COVID-19 on equine welfare and the equine industry in 2020

A review on the economic, welfare, and health impacts in horses and the equine sector due to Covid-19 in 2020 was discussed.

A Novel Likelihood-Based Model to Estimate SARS-CoV-2 Viral Titer from Next-Generation Sequencing Data

Background. The quantitative level of pathogens present in a host is a major driver of infectious disease (ID) state and outcome. However, the majority of ID diagnostics are qualitative. Next-generation sequencing (NGS) is an emerging ID diagnostics and research tool to provide insights, including tracking transmission, evolution, and identifying novel strains. Methods. We built a novel likelihood-based computational method to leverage pathogen-specific genome-wide NGS data to detect SARS-CoV-2, profile genetic variants, and furthermore quantify levels of these pathogens. We used de-identified clinical specimens tested for SARS-CoV-2 using RT-PCR, SARS-CoV-2 NGS Assay (hybrid capture, Twist Bioscience), or ARTIC (amplicon-based) platform, and COVID-DX software. A training (n=87) and validation (n=22) set was selected to establish the strength of our quantification model. We fit non-uniform probabilistic error profiles to a deterministic sigmoidal equation that more realistically represents observed data and used likelihood maximized over several different read depths to improve accuracy over a wide range of values of viral load. Given the proportion of the genome covered at varying depths for a single sample as input data, our model estimated the Ct of that sample as the value that produces the maximum likelihood of generating the observed genome coverage data. Results. The model fit on 87 SARS-CoV-2 NGS Assay training samples produced a good fit to the 22 validation samples, with a coefficient of correlation (r2) of ~0.8. The accuracy of the model was high (mean absolute % error of ~10%, meaning our model is able to predict the Ct value of each sample within a margin of ±10% on average). Because of the nature of the commonly used ARTIC protocol, we found that all quantitative signals in this data were lost during PCR amplification and the model is not applicable for quantification of samples captured this way. The ability to model quantification is a major advantage of the SARS-CoV-2 NGS assay protocol. Left. Observed genome coverage (y-axis) plotted against Ct value (x-axis). The best-fitting logistic curve is demonstrated with a red line with shaded areas above and below representing the fitted error profile. RIGHT: Model-estimated Ct values (y-axis) compared to laboratory Ct values (x-axis) with grey bars representing estimated confidence intervals. The 1:1 diagonal is shown as a dotted line. Conclusion. To our knowledge, this is the first model to incorporate sequence data mapped across the genome of a pathogen to quantify the level of that pathogen in a clinical specimen. This has implications in ID diagnostics, research, and metagenomics.

Performance Characteristics of Sequencing Assays for Identification of the SARS-CoV-2 Viral Genome

Background. As the SARS-CoV-2 (SCV-2) virus evolves, diagnostics and vaccines against novel strains rely on viral genome sequencing. Researchers have gravitated towards the cost-effective and highly sensitive amplicon-based (e.g. ARTIC) and hybrid capture sequencing (e.g. SARS-CoV-2 NGS Assay) to selectively target the SCV-2 genome. We provide an in silico model to compare these 2 technologies and present data on the high scalability of the Research Use Only (RUO) workflow of the SARS-CoV-2 NGS Assay. Methods. In silico work included alignments of 383,656 high-quality genome sequences belonging to variant of concern (VOC) or variant of interest (VOI) isolates (GISAID). We profiled mismatches and sequencing dropouts using the ARTIC V3 primers, SARS-CoV-2 NGS Assay probes (Twist Bioscience) and 11 synthesized viral sequences containing mutations and compared the performance of these assays using clinical samples. Further, the miniaturized hybrid capture workflow was optimized and evaluated to support high-throughput (384-plex). The sequencing data was processed by COVID-DX software. Results. We detected 101,432 viruses (27%) with > = 1 mismatch in the last 6 base pairs of the 3' end of ARTIC primers;of these, 413 had > = 2 mismatches in one primer. In contrast, only 38 viruses (0.01%) had enough mutations ( > = 10) in a hybrid capture probe to have a similar effect on coverage. We observed that mutations in ARTIC primers led to complete dropout of the amplicon for 4/11 isolates and diminished coverage in additional 4. Twist probes showed uniform coverage throughout with little to no dropouts. Both assays detected a wide range of variants (~99.9% coverage at 5X depth) in clinical samples (CT value < 30) collected in NY (Spring 2020-Spring 2021). The distribution of the number of reads and on target rates were more uniform among specimens within amplicon-based sequencing. However, uneven genome coverage and primer dropouts, some in the spike protein, were observed on VOC/VOI and other isolates highlighting limitations of an amplicon-based approach. Conclusion. The RUO workflow of the SARS-CoV-2 NGS Assay is a comprehensive and scalable sequencing tool for variant profiling, yields more consistent coverage and smaller dropout rate compared to ARTIC (0.05% vs. 7.7%).

Delivering physiotherapy outpatient assessment and treatment in a severe asthma clinic in the era of COVID-19

Introduction and ObjectivesThe global SARS-CoV-2 pandemic has forced clinicians to consider alternative methods of service provision to patients with respiratory conditions who were clinically vulnerable and/or advised to shield.Breathing pattern disorders (BPD) are a common comorbidity affecting approximately one third of patients with asthma. The respiratory physiotherapy team within the Portsmouth Severe Asthma Service (PSAS) recognised the need to continue to assess and deliver treatment for patients with BPD particularly at a time of heightened anxiety.Breathing retraining requires precise and highly specific assessment and treatment to ensure optimal outcomes and the decision to use a video conferencing platform was made to utilise the visual medium. To ensure quality service was being delivered, patients using the video conferencing platform to receive respiratory physiotherapy in the PSAS were asked for feedback.MethodsAt the end of every video consultation, written feedback was requested. Sixty-nine responses were received from July 2020-May 2021. Patients were asked to rate their physiotherapy consultation from very good to very poor;how they would prefer to receive treatment;if they would use this method of consultation again and the ease of use of the video consultation.ResultsOf the 69 responses:68/69 (98%) would use the service again58/69 (84%) rated the service as very good35/69 (51%) would choose video over face to face appointments23/69 (33%) would prefer to be seen face to face63/69 (91%) felt that accessibility of the video platform could be improvedQualitative feedback was also gathered from patients and included statements suchExcellent quality and a very thorough appointment.It was helpful to actually see a clinician face to face via video instead of a phone callConclusionsVideo consultations have proven to be a feasible and successful way of assessing BPD in asthma patients. Despite feedback regarding the ease of accessing the online platform being suboptimal, overarching positive responses to video consultations was received. With 51% favouring being seen via video consultation rather than face to face, this has wider implications for patients and the NHS including reduced travel time to appointments and reduced waiting room pressures.

Improving the accessibility of peak expiratory flow during the COVID-19 pandemic using a patient-friendly system

P78 Figure 1ConclusionThis electronic system re-vitalised the use of PEF in our asthma clinic;it is paper-light, patient-friendly and has increased our PEF diary responses, without additional cost or the requirement of a smart-phone. An average daily diurnal PEF variability >10% is valuable for the diagnosis of asthma and to assess asthma control. We continue to utilise PEF and have shared this resource across our local asthma networks. This is also likely to be beneficial in primary care to support annual asthma reviews and the requirement for at least two confirmatory diagnostic tests in the 2020/2021 NHS Quality and Outcomes Framework.

Corona Beat - Kicking The Sedentary Habit Induced By Prolonged Social Distancing

Due to COVID-19 restrictions, most people have limited access to their typical physical activities. However, these activities play a significant role for human beings: improving cognitive, physical, and social well-being. We introduce "Corona Beat", a proof-of-concept augmented reality customizable mobile application promoting physical activity in home environments. We designed four movement-based game scenarios that players can perform with their mobile phones: torso rotation, isometric stretching, isometric squat, and randomized rotation. We encourage these movements using COVID-19 particles, which players must defeat. In the future work, game designers/clinicians may use this work to physically train people while informing them about COVID-19.

SARS-CoV-2 NGS assay powered by biotia COVID-DX software

Background: COVID-19 had spread quickly, causing an international public health emergency with an alarming global shortage of COVID-19 diagnostic tests. We developed and clinically validated a next-generation sequencing (NGS)-based target enrichment assay with the COVID-DX Software tailored for the detection, characterization, and surveillance of the SARS-CoV-2 viral genome. Methods: The SARS-CoV-2 NGS assay consists of components including library preparation, target enrichment, sequencing, and a COVID-DX Software analysis tool. The NGS library preparation starts with extracted RNA from nasopharyngeal (NP) swabs followed by cDNA synthesis and conversion to Illumina TruSeq-compatible libraries using the Twist Library Preparation Kit via Enzymatic Fragmentation and Unique Dual Indices (UDI). The library is then enriched for SARS-CoV-2 sequences using a panel of dsDNA biotin-labeled probes, specifically designed to target the SARSCoV- 2 genome, then sequenced on an Illumina NextSeq 550 platform. The COVID-DX Software analyzes sequence results and provides a clinically oriented report, including the presence/absence of SARS-CoV-2 for diagnostic use. An additional research use only report describes the assay performance, estimated viral titer, coverage across the viral genome, genetic variants, and phylogenetic analysis. Results: The SARS-CoV-2 NGS Assay was validated on 30 positive and 30 negative clinical samples. To measure the sensitivity and specificity of the assay, the positive and negative percent agreement (PPA, NPA) was defined in comparison to an orthogonal EUA RT-PCR assay (PPA [95% CI]: 96.77% [90.56%-100%] and NPA [95% CI]: 100% [100%-100%]). Data reported using our assay defined the limit of detection to be 40 copies/ml using heat-inactivated SARS-CoV-2 viral genome in clinical matrices. In-silico analysis provided >99.9% coverage across the SARS-CoV-2 viral genome and no cross-reactivity with evolutionarily similar respiratory pathogens. Conclusion: The SARS-CoV-2 NGS Assay powered by the COVID-DX Software can be used to detect the SARS-CoV-2 virus and provide additional insight into viral titer and genetic variants to track transmission, stratify risk, predict outcome and therapeutic response, and control the spread of infectious disease.

Policy coordination and housing outcomes during COVID-19

Prior to the COVID-19 pandemic the housing system in Australia was under strain. Policy makers in Australia were braced for severe, detrimental impacts arising from the unfolding global pandemic. The response from all tiers of Australian government to these threats was rapid and comprehensive, and where required, coordinated. Broad estimates suggest that > $4 billion was allocated for new and expedited policy interventions at key points of the housing system. Good outcomes were achieved through coordinated action in some key policy areas, which provides broader lessons for how policy makers can address existing challenges in the housing system and respond to future crises with system-level implications. © 2020 Australian Housing and Urban Research Institute. All rights reserved.

Intelligent Size Matching Recommender System: Fuzzy Logic Approach in Children Clothing Selection

Choosing right-fit clothing is important for children since it is related to the conformity of clothes to the body, especially as we know that children normally engage in active routine activities. During the growth period, children grow-up rapidly in a different pattern. Nowadays, with internet and technology advancement, the online retail business has become the preferred shopping mode for internet-savvy customers, especially in the clothing and textile sector. The recent Coronavirus Pandemic has made online retail a necessity. Therefore, this research focuses on establishing a prototype of the children size matching recommender system, a "sizing advisor"for parents to identify the best clothes fitting which matches the requirement of their children's body size to the sizing of existing brands. The fuzzy logic approach was applied as a heart of the matching system where the triangular membership function has been used in predicting the suitable clothing size. Nine children aged between 6 years old and 12 years old were selected to test the system. The fit was validated by an expert in sizing. The research aims to provide a size matching system to increase buying satisfaction among parents while shopping for children's clothes online. The manufacturers, as well as small and medium-sized enterprises (SMEs) which engage in online retailing of children's clothing, may also benefit from reducing return and thus will help increase sales and profitability. © Published under licence by IOP Publishing Ltd.