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This article reports on the findings from a technology-enhanced teacher learning project where the SETTVEO app (Self Evaluation of Teacher Talk through Video Enhanced Observation) was used to support teachers' reflective practices and professional development. Participants in the project were a group of 40 student teachers (ST) from Hong Kong, who took part in a teaching practicum taught online owing to COVID-19 restrictions. They formed online professional learning communities (PLCs) with peers and tutors, shared their class recordings (tagged using the on SETTVEO app), and reflected on their teaching through weekly discussions. This study aims to characterize teacher learning mediated by video technology and dialogue, and to evaluate the impact of the app on STs' reflective practices and emerging Classroom Interactional Competence (CIC, Walsh 2013). In this article, we focus on an individual ST's development over a period of eight weeks. Two sources of data are transcribed and analysed using an applied Conversation Analysis (CA) method: the first records the teacher's interactions while teaching, the second their dialogic reflections based on observations of these class recordings. Findings from the study enhance our understandings of the role of technology in influencing classroom practice and highlight its importance in promoting teacher noticing and professional development. © The Author(s) 2023.
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Lung fibrosis quantification from CT scans is prone to large inter and intra observer variability and its correlation with PFT is essential in the definition of disease progression. There is the need for a reliable and reproducible tool for abnormalities quantification. For this reason, a deep learning abnormalities quantification model was used to explore the correlation with PFT in ILD patients. The abnormalities segmentation model is based on 2D U-Net combined with Res Next as encoder and deep supervision and was trained on axial unenhanced chest CT scans of 199 COVID-19 patients and externally validated on 50 COVID-19 patients. Whole lungs were segmented using RadiomiX toolbox. Validation of the quantification performance was explored in a cohort of 20 ILD patients. The model performed the automatic segmentation of all abnormalities and calculate the ratio on the total lung volume ((abnormalities volume/whole lungs volume) * 100). This value is then correlated with the Forced Vital Capacity (FVC) and Diffusion Lung Capacity for carbon monoxide (DLCO) for each patient with Pearson correlation coefficient (rho). The deep learning segmentation algorithm achieved good performances (mean DSC 0.6 +/- 0.1) on the external test set. The percentage volume of disease region correlated with FVC and DLCO were the rho = -0.70402, -0.58133, respectively (P <. 001 for all). The developed algorithm performed similarly to radiologists for disease-extent contouring, which correlated with pulmonary function to assess CT images from patients with ILD. This automatic quantification tool could help in the prognosis and diagnosis of ILDs, based on the lung abnormalities extent.
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Background. Vaccination strategies that provide enhanced immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are needed. We evaluated the safety and immunogenicity of a bivalent omicron containing vaccine, mRNA-1273.214 (50 mug), administered as a second booster dose in adult participants. Methods. In this ongoing phase 2/3 trial, 50 mug of the bivalent vaccine mRNA-1273.214 (25 mug each ancestral Wuhan-Hu-1 and omicron BA.1 spike mRNAs) or 50 mug of the authorized mRNA-1273 were administered as second boosters in adults who previously received a 2 dose (100 mug) primary series and a first booster (50 mug) dose of mRNA-1273 (>= 3 months prior). Primary objectives were safety and reactogenicity and immunogenicity 28 days post-booster dose. Results. In participants with no prior SARS-CoV-2 infection who received booster doses of mRNA-1273.214 (n=334) or mRNA-1273 (n=260), neutralizing antibody (nAb) geometric mean titers (GMTs [95% confidence interval (CI)]) against omicron BA.1 were 2372.4 (2070.6-2718.2) and 1473.5 (1270.8-1708.4), respectively. The model-based GMT ratio (GMR [97.5% CI]) of mRNA-1273.214 compared to mRNA-1273 was 1.75 (1.49-2.04), meeting the pre-specified superiority criterion against omicron BA.1. The pre-specified criterion for non-inferiority against the ancestral SARS-CoV-2 strain was also met. Additionally, mRNA-1273.214 elicited higher GMTs (727.4 [632.8-836.1]) than mRNA-1273 (492.1 [431.1-561.9]) against omicron subvariants BA.4/BA.5 [GMR (95% CI) 1.69 [1.51-1.90])]. Binding antibody responses against alpha, beta, gamma, delta, and omicron were numerically higher in the mRNA-1273.214 group compared to mRNA-1273. mRNA-1273.214 GMTs were consistently higher across age (18-< 65 and >= 65 years) and pre-booster SARS-CoV-2 infection subgroups (Figure). Safety and reactogenicity were similar for both vaccine groups. Conclusion. The bivalent omicron containing mRNA-1273.214 elicited superior nAb responses against omicron 28 days post-immunization compared to mRNA-1273 regardless of age and prior SARS-CoV-2 infection;no new safety concerns were identified. (Figure Presented).
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Background. SARS-CoV-2 vaccination reduces the risk and severity of coronavirus disease 2019 (COVID-19), but immunogenicity may be reduced in patients undergoing hematopoietic stem cell transplantation (HSCT). The variables that impact the humoral response, such as age, gender, disease and transplant type, prior treatments, and vaccine type, have not been comprehensively described. Methods. A retrospective review was conducted at a single-centre of HSCT recipients who received COVID-19 vaccinations between 2020 and 2021. Participants were included if >18 years and had received at least a single dose of Pfizer, Moderna or Johnson & Johnson (J&J) vaccine. Anti-Spike (S) IgG titers were quantitatively measured at provider discretion during routine care using the Roche Elecsys Anti-SARS-CoV-2 spike immunoassay and categorized as Responders (< 0.8U/mL) and Non-responder (>0.8). Multivariate logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for Responders vs Non-responders. Controlled risk factors included;Age, disease, treatments, and history of graft-versus-host disease (GVHD). Results. Of 117 HSCT patients assessed, 59 (50.4%) were female, 106 (90.6%) were white, and the median age was 62.5 years (interquartile range [IQR, 49.9-67.8). Vaccinations were administered at a median of 179 days post-transplant (IQR 319 - 105) and antibody responses were measured at a median of 135.5 days post-vaccination (IQR 190-50). 106(90.6%) were responders with a mean titre of 1141.5U/mL (SD=1095.3). 35% had Low (< 100U/mL) titres. Being Female (OR 0.02, 95%CI 0.003 - 0.6) was associated with a slightly higher odds of being a responder. Conclusion. Hematopoietic stem cell transplant recipients demonstrated a high prevalence of anti-S IgG antibody positivity following COVID vaccination. However, neither patient characteristics nor treatment regimens were seen to be strongly associated with anti-S protein positivity among HSCT recipients. More studies are needed to further characterize patient and treatment characteristics that correlate with seroprotection among these patients.
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The Fourth Industrial Revolution - Industry 4.0 (I-4.0) provides innovators new commercial promise and challenges. For the first time, service-based disruptive technologies are included as harbingers of the Schumpeterian economic industrial waves. The strategic, tactical, and operational importance of disruptive technologies and their resultant discontinuous innovations that underpin a new industrial wave are game-changing for state, regional, national, and global economies. However, there are always barriers, both technical and social, to new technology product adoption. The COVID-19-induced industry forcing function has created a ‘low-touch economy', changing business action and creating a new normal. We focus on the challenges to the realisation of I-4.0. We use the internet of things (IoT) as our exemplar. IoT is the first service-based technology to support an industrial revolution. It challenges the traditional view of how firms compete. It is creating wealth and jobs and is an agent of societal transformation. Copyright © 2022 Inderscience Enterprises Ltd.
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The destitution of image data and corresponding expert annotations limit the training capacities of AI diagnostic models and potentially inhibit their performance. To address such a problem of data and label scarcity, generative models have been developed to augment the training datasets. Previously proposed generative models usually require manually adjusted annotations (e.g., segmentation masks) or need pre-labeling. However, studies have found that these pre-labeling based methods can induce hallucinating artifacts, which might mislead the downstream clinical tasks, while manual adjustment could be onerous and subjective. To avoid manual adjustment and pre-labeling, we propose a novel controllable and simultaneous synthesizer (dubbed CS$$
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The upheaval brought by the arrival of the COVID-19 pandemic has continued to bring fresh challenges over the past two years. During this COVID-19 pandemic, there has been a need for rapid identification of infected patients and specific delineation of infection areas in computed tomography (CT) images. Although deep supervised learning methods have been established quickly, the scarcity of both image-level and pixel-level labels as well as the lack of explainable transparency still hinder the applicability of AI. Can we identify infected patients and delineate the infections with extreme minimal supervision? Semi-supervised learning has demonstrated promising performance under limited labelled data and sufficient unlabelled data. Inspired by semi-supervised learning, we propose a model-agnostic calibrated pseudo-labelling strategy and apply it under a consistency regularization framework to generate explainable identification and delineation results. We demonstrate the effectiveness of our model with the combination of limited labelled data and sufficient unlabelled data or weakly-labelled data. Extensive experiments have shown that our model can efficiently utilize limited labelled data and provide explainable classification and segmentation results for decision-making in clinical routine.
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A 27-year-old man presented to Accident and Emergency with an itchy rash over the thighs and buttocks. This followed 2 days of fever, headache and malaise. His past medical history was unremarkable and there was no regular medication use. He was unvaccinated. There was no history of previous erythema multiforme (EM) or herpes simplex virus (HSV) infection. He was febrile but otherwise haemodynamically stable. Clinically, over the thighs and buttocks there was a symmetrical rash consisting of striking urticated targetoid lesions. Some had a dusky centre and had coalesced over the thighs. There was no mucosal involvement. A SARS-CoV-2 polymerase chain reaction test was positive. Mycoplasma serology and swabs for HSV were negative. Other bloods were unremarkable. A skin biopsy from affected skin showed spongiosis and a mild dermal lymphocytic infiltrate. There was an absence of necrotic keratinocytes. He was treated with 5 days of prednisolone (30 mg) and potent topical steroids. There was complete clinical resolution of the rash in a week. In the published literature there are a small number of EM-like eruptions in the context of COVID-19 infection. Similar to our patient, skin biopsies often show features not typical of EM, including spongiosis and a lymphocytic perivascular and interstitial infiltrate (Torrelo A, Andina D, Santonja C et al. Erythema multiforme-like lesions in children and COVID-19.
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Background: Communicative rehabilitation can be complex and challenging for children with an acquired brain injury (ABI) who use augmentative and alternative communication (AAC) systems. The development of communicative competence (CC) in children with use AAC systems is in itself complex and multifaceted (Light, 1989, Light and McNaughton, 2014) and it can be challenging for clinicians to target multiple competencies effectively through direct intervention. The Brick-by-Brick™ programme (previously known as LEGObased therapyR) has an evidence base routed in research with verbal young people with Autism Spectrum Condition. The programme is a collaborative play therapy originally designed as a social intervention to target the development of social communication and interaction skills (LeGoff, 2004). Introduction: The presentation aims to explore a use of the Brick-by-Brick™ programme with children with ABI who use AAC to support or replace their verbal communication, as well as the areas of potential clinical need for adaptations to its delivery to increase access for this client group. It will also discuss the theory behind adaptations and the need for evidence to support decision making clinically around this topic. The aims and methods of the presenter's current research will be discussed using Janice Light's framework of communicative competence (Light, 1989;Light and McNaughton, 2012) to discuss areas of competence during the presentation. Methods: The research agenda of an embedded quasiexperimental mixed methods design will be shared, along with considerations for the commencement of data collection in a country still significantly affected by the health, social, and educational repercussions of the Covid-19 pandemic. Clinical adaptations to the programme made by the presenter in her role as highly specialist speech and language therapist will be discussed and linked to her current research. Discussion, Conclusions and Recommendations: Adapting the delivery of the Brick-by-Brick™ programme for use with AAC users with ABI is not without difficulties, but these are not insurmountable. Practical and theoretical recommendations for the adaptation of the programme in both educational and healthcare rehabilitation settings will be shared. Future thoughts on the development of the current research base will also be discussed.
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Asthma is a very prevalent condition. A significant proportion of patients with asthma will engage in travel for work or leisure purposes. Patients may be fearful of travel, especially during the current COVID-19 global pandemic. However, there are health benefits to be obtained, including leaving an area of high air pollution and travelling to an area of lower air pollution, travelling to high altitude, the beneficial effects of a low trigger environment and the psychological benefits associated with travel. Travel can be associated with improved diet and increased vitamin D exposure. Caution should be taken with alcohol consumption as it may worsen asthma. Whilst bariatric surgery has been shown to improve asthma symptoms and control, there are dangers associated with bariatric surgery tourism that the traveller should be made aware of. Travellers with asthma may experience jet lag and a worsening in their symptoms. Caution is required around exogenous melatonin use. Optimal asthma control pre-travel is essential. The destination should be carefully considered, in terms of air pollution, altitude and possible environmental triggers. Pre-travel, written asthma management plans should be reviewed and updated if necessary. Patients should carry more asthma medications than they think is necessary, including oral corticosteroids and a pressurised metered dose inhaler via spacer. Travellers with asthma should have a self-management plan in the event of exacerbations occurring during travel.
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OBJECTIVES: To examine levels of psychological distress among higher education students in Ireland overall and across a range of personal, higher education, and socioeconomic characteristics, prior to the COVID-19 pandemic. METHODS: A cross-sectional online survey of college students in Ireland was undertaken in 2018. Data on 5201 students from 13 higher education institutions (HEIs) were analyzed. Stress, anxiety, and depression symptom scores based on the Depression, Anxiety and Stress Scale (DASS-21) were calculated and reported, with statistical testing used to compare across groups. RESULTS: Overall, 29.6% and 19.1% of respondents were classified in the mild to moderate and severe to extremely severe range for depression respectively. The corresponding proportions were 25.9% and 20.7% for anxiety, and 24.5% and 14.8% for stress. Differences across groups included higher levels of psychological distress for transgender and female students compared to males (p < 0.01), for gay/lesbian/bisexual students compared to heterosexuals (p < 0.01), for undergraduates compared to postgraduates (p < 0.01), for students from intermediate/technical/service/unskilled social classes compared to professional/self-employed social classes (p < 0.01), and for those with financial difficulties compared to those without financial difficulties (p < 0.01). CONCLUSIONS: Rates of psychological distress were high amongst college students in Ireland prior to the COVID-19 pandemic, with substantial differences across groups. Due to study limitations, such as possible selection bias, the findings need replication. Further research is needed to determine the impact of the pandemic on the prevalence of mental illness in this population.
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Introduction: The COVID-19 epidemic left high proportion of healthcare workers (HCWs) faced with considerable levels of anxiety, depression, and insomnia. Previous studies have shown excessive workload and inadequate working conditions are two main issues among HCWs. Assessing QoWL has been considered as an important way of understanding how HCWs evaluate their work environment. Material and Methods: A cross section survey among frontline HCWs from China and UK (n = 345) was undertaken based on seven dimensional QoWL factors : General Well-Being (GWB);Home-Work Interface (HWI);Job & Career Satisfaction (JCS);Control at Work (CAW), Working Conditions (WCS);Stress at Work (SAW);employee engagement (EEN). Cronbach α was used to measure the internal consistency within each domain and to test the exploratory factor structure confirmatory factor analysis (CFA) was applied. Descriptive analysis and One-way ANOVA was performed to examine the association between demographic and job characteristics with QoWL. Ethics clearance was granted by faculty ethics committee. Results: Acceptable Cronbach α score, and CFA were achieved. Overall, 72.8% of the HCWs confirmed working under pressure during the pandemic and 54.2% felt excessive level of stress associated with workload. Significant differences were found between gender and three dimensions, i.e. EEN (F = 6.51, p = 0.011), GWB (F = 3.91, p =0.049), HWI (F = 5.22, p = 0.023). Conclusions: The study conclude organisations and related stakeholders should invest in workplace programmes aimed at alleviating stress at work and excessive workload issue among frontline HCWs.
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Perioperative oncological therapies resulting in pathological complete response (pCR) in diffuse-type distal gastric adenocarcinoma are extremely rare. We report a case of locally advanced (cT3 N2 M0) diffuse-type distal gastric adenocarcinoma treated with 'total neoadjuvant' FLOT (eight cycles), due to the COVID-19 pandemic, and laparoscopic radical subtotal gastrectomy with D2 lymphadenectomy. The patient demonstrated a progressive radiological response on positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-d-glucose integrated with computed tomography (18F-FDG PET-CT) and pCR in the resected specimen (ypT0 N0). As far as we are aware, this is the first case of pCR in locally advanced T3 N2 diffuse distal gastric cancer to be reported in the literature. It introduces a novel approach of total neoadjuvant chemotherapy with 18F-FDG PET-CT to assess response, combined with radical minimally invasive surgical management to provide optimal care for patients with gastric cancer.